Staff Data Engineer

🏢 Summary: Principal Data Platform Engineer role focused on architecting and implementing a centralized Databricks lakehouse platform, including governance, ETL frameworks, and large-scale data migration. The position centers on building scalable, cost-efficient, and well-governed data infrastructure across multiple product lines. It involves leading multi-terabyte legacy migrations and establishing robust platform operations for analytics and AI workloads. 🗂️ Requirements: 5-8 years in data engineering or data platform roles, 3+ years hands-on experience with Databricks, Production experience with Unity Catalog and multi-catalog governance, Expert experience with Delta Lake optimization at multi-TB scale, Strong hands-on experience with Delta Live Tables, Experience with Databricks Workflows for orchestration and monitoring, Strong proficiency in PySpark and Databricks SQL, Experience designing unified schemas across disparate data sources, AWS experience including S3, IAM, VPC, Infrastructure-as-code experience (Terraform preferred), Experience leading at least one significant platform build or migration project, Ability to architect data platforms and document technical decisions 📃 Skills: Databricks, UnityCatalog, DeltaLake, DeltaLiveTables, PySpark, DatabricksSQL, AWS, S3, IAM, VPC, Terraform, SQL, ETL, Z-ordering, Compaction, Clustering 🏢 Description: Exactera has offices in New York City, Tarrytown NY, San Diego, CA, London, and Argentina. The Role As Principal Data Platform Engineer, you'll architect and implement our centralized data platform on Databricks. You'll establish governance patterns using Unity Catalog, optimize for cost and performance at scale, and enable our existing Data Engineers to build confidently on the platform. This is a data infrastructure role—focused on pipelines, storage, governance, and platform operations. The Business Challenge We operate multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning), each with distinct databases containing enterprise financial data—journal entries, general ledgers, and financial statements. Our immediate challenge is migrating multi-terabyte datasets from legacy systems to a unified Databricks lakehouse while establishing governance patterns that enable multi-product operations at scale. What You'll Build Data Structuring: Design data models and implement unified schemas across multiple disparate product lines. Unity Catalog Architecture: Design and implement multi-catalog governance strategy supporting data isolation, cross-product data sharing, and comprehensive lineage tracking across our product portfolio Delta Lake Optimization: Establish patterns for Z-ordering, compaction, and liquid clustering at multi-TB scale. Define table structures, partitioning strategies, and retention policies that balance query performance with storage costs ETL Pipeline Framework: Build declarative pipeline patterns using Delta Live Tables. Create orchestration workflows for ingesting data from internal sources such as SQL databases and S3 Third Party Integrations: Integrate with third party data sources such as ERP systems (Netsuite etc.) and external data providers (S&P etc.) with automated ingest, robust error handling and monitoring. Platform Operations: Implement cost monitoring and optimization strategies, establish data quality frameworks, create self-service patterns enabling Data Engineers to work independently while maintaining governance standards Business Problems You'll Solve Key Legacy Product Migrations: Lead the architecture for migrating multi-terabyte datasets from legacy systems to Databricks—establishing patterns that will be reused across multiple product lines Multi-Product Data Architecture: Design Unity Catalog structures enabling secure data separation between product lines while allowing controlled cross-product analytics where appropriate Cost-Efficient Scale: Build infrastructure that scales efficiently—through intelligent caching, query optimization, and compute management strategies that avoid linear cost growth Platform Reliability: Establish monitoring, alerting, and data quality validation ensuring the platform operates reliably as foundation for both analytics and AI workloads Required Experience Databricks Expertise (Required) Unity Catalog: Production experience with multi-catalog governance, metastore design, and lineage tracking. Data Structuring: Experience designing and building unified schemas across multiple disparate product lines. Delta Lake: Expert-level experience with Z-ordering, compaction, liquid clustering, and performance tuning at multi-TB scale Delta Live Tables: Strong hands-on experience building declarative ETL pipelines, including change data capture and expectations/constraints Databricks Workflows: Experience with job orchestration, scheduling, and operational monitoring Business Intelligence: Experience enabling company-wide analytics and reporting with modern business intelligence tools and maintaining source of truth data and metrics. PySpark & Databricks SQL: Strong proficiency for code review, performance tuning, and query optimization Core Platform Engineering 5-8 years in data engineering or data platform roles, with 3+ years hands-on Databricks experience Track record leading at least one significant platform build or migration project AWS experience (S3, IAM, VPC) with ability to collaborate on infrastructure decisions Infrastructure-as-code experience (Terraform preferred) Technical Leadership Demonstrated ability architecting data platforms from first principles and defending technical decisions Strong written and verbal communication— document architecture decisions and present to both technical and business stakeholders Preferred But Not Required Experience with financial data, accounting systems (NetSuite), or enterprise ERP platforms Background building platforms that serve AI/ML workloads (experience preparing data for downstream ML consumption, RAG and retrieval, and LLMs. Understand advanced intelligence concepts such as relationship surfacing with knowledge graphs Familiarity with data governance frameworks and compliance requirements for regulated industries What We Offer:(The following only applies to US-based positions) A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. About Us: At Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. With over $100 million in funding from Savant Venture Fund and Insight Partners, we are poised for growth. We are committed to diversity, inclusion, and equal opportunities for all.

🏢 Summary: Principal-level Product Manager role owning the strategy and roadmap for an AI-native, agentic platform that powers compliance-grade tax analysis on trusted data. The position defines how AI agents and practitioners access, use, and govern data, ensuring defensible, auditable outputs in regulated tax workflows. You will work closely with AI and Data Engineering leadership to shape platform capabilities, guardrails, and measurable practitioner outcomes. 🗂️ Requirements: 10+ years in product management, Experience owning technical platform, data, or ML products, Proven ownership of AI or ML platform from ambiguity to production, Strong understanding of lakehouse architectures and data contracts, Knowledge of agentic AI systems, retrieval, and tool calling, Experience designing guardrails, evaluation, and human-in-the-loop systems, Ability to define compliance-grade, auditable product requirements, Experience working cross-functionally without positional authority, Hands-on use of AI tools in daily work 📃 Skills: AI, ML, Lakehouse, Databricks, Delta, Retrieval, MCP, Data, Lineage, Evaluation, Guardrails, SaaS 🏢 Description: About the Role Exactera helps large multinationals handle complex tax work: transfer pricing, R&D tax credits, indirect tax, and audit defense. The company is moving from a software-and-services model to an AI-native platform that performs the work itself, with tax practitioners applying judgment where defensibility requires it. This role owns the product direction for the agentic platform behind that shift: the system that enables AI agents and practitioner tools to run tax analysis on trusted, current data. The data foundation (a lakehouse, external sources, and the contracts that keep them reliable) is the substrate. The product defines what agents and practitioners can do with it. You work directly with the Principal AI Engineer, who owns the AI/ML architecture, and the Principal Data Engineer, who owns the data tier. You own what the platform does, in what order, and why. Because you define how practitioners and agents use AI, you work deeply in these tools yourself. What You’ll Do The six outcomes that define success in the first 18 months: O1. Own the product strategy and roadmap for the platform. You own what the platform is for and what it builds next. The roadmap ties to practitioner outcomes rather than feature counts. When priorities compete across engineering, product, and practice teams, you decide and keep everyone aligned. O2. Define what compliance-grade means for this platform. Tax work must be defensible. You set product requirements that make platform output trustworthy: where results must be deterministic, what guardrails constrain agent behavior, how tool access is scoped, and what must be auditable. You determine where human judgment remains in the loop. O3. Own the agentic access surface. You own the interface AI agents and practitioner tools use to reach data and act on it, the contracts behind it, and the limits on agent capabilities. How this surface works determines how the entire platform is used. O4. Treat the data foundation as a product. With the Principal Data Engineer, you define contracts between data producers and consumers, including schema, quality, and freshness commitments practitioners can rely on. O5. Make external data a platform capability. You decide which regulatory, financial, and third-party data sources matter, how they appear in the product, and how to balance coverage, cost, and reliability. O6. Measure success by practitioner outcomes. Success is defined by faster, more accurate work with less manual effort. A production pipeline that does not improve a practitioner’s day is not successful. What We’re Looking For Required 10+ years in product management, with significant experience in technical platform, data, or ML products. Experience owning a platform or major product area at Principal-level scope across teams without positional authority. Ability to set direction across a modern data platform, including understanding of lakehouse and medallion patterns, data contracts, quality, and lineage. Track record of owning AI or ML platform initiatives from ambiguous problem definition to production. Strong understanding of agentic AI systems and data access patterns, including retrieval and tool calling. Experience designing AI systems where correctness and defensibility matter, including evaluation, guardrails, and human-in-the-loop workflows. Ability to define and measure platform success through practitioner results. Clear communication across engineering, product, and practice teams. Active use of AI tools in day-to-day work. Preferred Experience in tax, financial reporting, regulatory compliance, or other regulated, data-intensive domains. Experience building or governing data products, including external data sourcing and licensing trade-offs. Hands-on familiarity with Databricks, Delta Lake, or comparable lakehouse platforms in production. Background in tech-enabled services or SaaS-to-services transitions. Experience building a platform or major product area from an early stage. What We Offer A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits such as a dependent care savings plan, pet insurance, will preparation, and an employee assistance program.

🏢 Summary: Lead Data Engineer role focused on driving architecture and leading a team to build scalable, secure ETL/ELT pipelines and analytics-ready data models on modern cloud platforms. The position combines hands-on engineering with technical leadership, ensuring high standards in governance, observability, and performance optimisation. You will shape data infrastructure that supports large-scale analytics across the organisation. 🗂️ Requirements: Proven experience leading data engineering or analytics engineering teams, Strong programming skills in SQL, Strong programming skills in Python, Hands-on experience with Airflow or Prefect in production, Deep practical experience with dbt, Experience with Snowflake or Databricks at scale, Strong knowledge of dimensional modelling and SCD strategies, Experience implementing data quality and governance frameworks, Experience with CI/CD and automated testing in data systems 📃 Skills: SQL, Python, Airflow, Prefect, dbt, Snowflake, Databricks, ETL, ELT, CI/CD, SCD, Dimensional, Git, IaC 🏢 Description: ABOUT THE COMPANY Our client is a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the infrastructure you lead will have real consequence across the organisation. ABOUT THE ROLE We're looking for a Lead Data Engineer to combine deep technical expertise with hands-on team leadership, guiding a team of data engineers building and maintaining ETL/ELT pipelines, data models, and governance frameworks that power analytics and reporting across the organisation. This is a technical leadership role — you'll drive architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable data solutions. You'll collaborate closely with stakeholders to align technical work with business objectives, champion governance and observability standards, and foster a culture of continuous improvement. The expectation is that you're equally effective in an architecture review as you are pairing with an engineer on a tricky pipeline problem. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data engineers, promoting collaboration, knowledge sharing, and professional growth. Set the standard for engineering quality and hold the bar consistently. Architecture and pipeline design Drive architectural decisions for ETL/ELT pipelines, orchestration frameworks (Airflow/Prefect), and transformation layers (dbt). Facilitate architecture reviews and contribute to design decisions for scalable, fault-tolerant systems. Analytics data modelling Oversee design and implementation of analytics-ready data models — dimensional schemas, SCD strategies, and semantic layers — that internal teams can build on reliably. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. Platform optimisation Manage performance tuning and cost optimisation for Snowflake, Databricks, and related cloud data platforms at scale. Governance and observability Champion governance, observability, and compliance frameworks across all data workflows — including data quality, lineage tracking, and multi-tenant environment controls. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure timely delivery aligned with business objectives. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or analytics-focused development teams — mentoring engineers, driving architectural decisions, and owning delivery outcomes. SQL and Python Strong programming skills in both SQL and Python, applied to production data systems at scale. ETL/ELT orchestration Hands-on experience with orchestration tools — Airflow and/or Prefect — in production pipeline environments. dbt expertise Deep practical experience with dbt for transformation workflows and analytics modelling, including testing, documentation, and modular project design. Snowflake and Databricks Familiarity with Snowflake and/or Databricks for large-scale data processing, including performance tuning and cost management. Data modelling principles Solid understanding of data modelling principles, incremental strategies, and schema design for analytics — dimensional modelling, SCDs, and semantic layer design. Governance and data quality Knowledge of data quality frameworks, lineage tracking, and governance in multi-tenant environments. Software engineering practices Familiarity with CI/CD, automated testing, and infrastructure-as-code practices applied to data systems. Communication and stakeholder management Strong communication skills with the ability to operate confidently across technical teams and business stakeholders. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 270,000 – 406,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements, hybrid model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: The role focuses on designing and building scalable, cloud-native data platforms to enable advanced analytics and reporting across a large internal data ecosystem. It involves developing distributed data pipelines, lakehouse architectures, and optimised data warehousing solutions with strong emphasis on performance, governance, and reliability. The position requires deep technical expertise in big data technologies and cloud-native infrastructure, including on-call responsibility for platform stability. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Commercial experience with Apache Spark for distributed data processing, Hands-on experience with Delta Lake and/or Apache Iceberg in production, Experience with dbt for SQL transformations, Experience with Databricks and Snowflake, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Understanding of performance tuning and cost optimisation in large-scale data systems, Ability to participate in on-call rotations 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. Over 75% of our business has transitioned to our cloud platform, and we are making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the infrastructure you build will have real consequence. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As an Advanced Data Platform Engineer, you'll design and implement scalable, cloud-native data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services to support diverse analytical use cases at enterprise scale. The role emphasises technical depth — performance optimisation, governance best practices, and the kind of engineering rigour that keeps vast datasets accessible, secure, and compliant. You'll work closely with internal teams to deliver curated datasets and self-service analytics capabilities, and you'll participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems design Design and implement complex data pipelines and distributed systems using Spark and Python, applying clean code principles, modular design, CI/CD, automated testing, and thorough code reviews. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Apache Iceberg, ensuring reliability, performance, and long-term maintainability at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Deliver curated datasets and self-service analytics capabilities that empower internal stakeholders to explore data independently. Data warehousing optimisation Optimise Databricks and Snowflake environments for performance and scalability. Drive cost optimisation and performance tuning across Spark jobs and cloud-native infrastructure. Observability and governance Implement observability and governance frameworks including data lineage tracking and compliance controls, ensuring data remains secure and auditable. On-call participation Participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT WE LOOK FOR Python and SQL Strong programming skills in Python and SQL — the foundation for everything you'll build here. Apache Spark Solid experience with Spark for distributed data processing at scale, including performance tuning and optimisation. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the tradeoffs and have used these in production environments. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and SQL transformation pipelines. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Scalability and cost optimisation Understanding of performance tuning, scalability strategies, and cost optimisation for large-scale data systems. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 160,000 – 240,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Senior Data Platform Engineer role focused on building and optimising a cloud-native lakehouse platform for large-scale analytics and reporting. The position involves designing distributed data pipelines, enabling self-service analytics, and implementing governance and observability frameworks using modern data technologies. You will work with Spark-based systems and integrated data warehousing solutions to deliver scalable, reliable data platforms. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Hands-on experience with Apache Spark in production environments, Experience with Delta Lake and/or Apache Iceberg in production, Practical experience with dbt for data transformations, Experience with Databricks and Snowflake, Understanding of data governance and lineage in large-scale environments, Familiarity with Kubernetes and Docker, Experience with CI/CD and automated testing practices, Ability to participate in on-call rotations 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the platforms you build will have real consequence across the organisation. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As a Senior Data Platform Engineer, you'll combine strong software engineering principles with deep data expertise to build robust, cloud-native platforms that process large-scale datasets efficiently and enable internal teams to build reporting and analytics on top of them. The role emphasises cloud-native architecture, lakehouse integration, data warehousing, and governance best practices. You'll work on systems using Apache Spark, Delta Lake, and Iceberg, and help deliver curated data models and self-service analytics capabilities to internal stakeholders. You'll also participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems Design and implement scalable data pipelines and distributed systems using Spark and Python to process and transform large-scale datasets for analytics and reporting. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Iceberg, ensuring data reliability, versioning, and performance optimisation at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Collaborate with internal teams to deliver curated datasets and self-service analytics capabilities for reporting and advanced use cases. Data warehousing optimisation Integrate and optimise Databricks and Snowflake for scalable storage and query performance. Drive performance tuning and cost optimisation across Spark jobs and cloud-native environments. Governance and observability Implement observability and governance frameworks including data lineage, quality checks, and compliance controls. Build platforms that allow secure and compliant access to diverse data sources. Engineering best practices Apply and champion clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. On-call participation Participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT WE LOOK FOR Python and SQL Strong programming skills in both Python and SQL, applied to production data platform work at scale. Apache Spark Solid hands-on experience with Spark for distributed data processing, including performance tuning in production environments. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You've applied these in production and understand the trade-offs in real-world scenarios. dbt and analytics tooling Practical experience with dbt for transformation workflows. Familiarity with Databricks and Snowflake for large-scale analytics workloads. Data governance and compliance Understanding of data governance, lineage tracking, and compliance requirements in large-scale, multi-tenant data environments. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 208,000 – 312,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Lead Distributed Data Platform Engineer responsible for architecting and delivering enterprise-scale lakehouse and distributed data platforms to enable advanced analytics and reporting. The role combines hands-on technical leadership with team mentorship, driving scalable, secure, and high-performance data solutions in cloud-native environments. You will guide architectural decisions, enforce engineering best practices, and ensure platform reliability at scale. 🗂️ Requirements: Proven experience leading data engineering or platform teams, Strong programming skills in Python, Strong programming skills in SQL, Hands-on experience with Apache Spark in production, Experience with Delta Lake and/or Apache Iceberg in production, Experience designing distributed systems and lakehouse architectures, Experience building scalable data pipelines, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Experience working in cloud-native environments 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD, Java, Scala, Rust 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the platform you lead will underpin how the entire organisation accesses and acts on its data. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As Lead Distributed Data Platform Engineer, you'll combine deep technical expertise with hands-on team leadership — guiding a team in designing and maintaining data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services at enterprise scale. You'll lead architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable solutions. The role emphasises technical leadership, governance best practices, and a culture of innovation and continuous improvement. You'll also participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data platform engineers, promoting collaboration, knowledge sharing, and professional growth. Set and maintain high engineering standards across the team. Distributed systems architecture Drive architectural decisions for distributed systems and lakehouse platforms using Spark, Delta Lake, and Iceberg. Facilitate architecture reviews and contribute to design decisions for fault-tolerant, future-ready systems. Data pipeline and platform delivery Oversee design and implementation of scalable data pipelines and analytics workflows, ensuring they are reliable, performant, and maintainable at scale. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all platform engineering work. Performance and cost optimisation Manage performance tuning, scalability strategies, and cost optimisation across cloud-native environments and large-scale distributed workloads. Governance and observability Champion governance, observability, and compliance frameworks across all data platforms — ensuring data remains accessible, secure, and auditable. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure delivery aligns with business objectives and analytics needs. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or platform development teams — mentoring engineers, owning architectural decisions, and driving delivery outcomes. Python and SQL Strong programming skills in both Python and SQL applied to production data platform work at scale. Apache Spark Hands-on experience with Spark for distributed data processing, including performance tuning and optimisation in production environments. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the trade-offs and have applied these technologies in production at scale. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and large-scale data processing. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data platform systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Communication and stakeholder management Strong communication skills with the confidence to operate across engineering teams, cross-functional partners, and senior leadership. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. Exposure to service mesh and advanced orchestration patterns. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 270,000 – 406,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Staff Data Analyst role focused on building and leading advanced analytics strategy to drive customer insights, predictive modeling, and AI-enabled decision-making. The position involves designing semantic data models, co-creating scalable data pipelines, and delivering high-impact dashboards and command center solutions. You will leverage cloud and big data technologies to enable data-driven strategy across cross-functional teams. 🗂️ Requirements: BS in Computer Science, MIS or related technical degree, 7+ years experience in Data Analyst, Data Engineer or BI Developer role, Advanced SQL proficiency, Experience building reports and dashboards in Tableau or similar tools, Experience with ETL processes and data pipeline development, Programming experience in Python and Java, Experience working with Databricks and Snowflake, Experience with predictive modeling and advanced analytics, Ability to design data models and semantic layers, Experience collaborating with Engineering on scalable data solutions 📃 Skills: SQL, Python, Java, Databricks, Snowflake, Tableau, ETL, AI, ML, NLP, BI, DataModeling, PredictiveModeling, Cloud, Telemetry 🏢 Description: Secure Every Identity, from AI to HumanIdentity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.The Data & Insights Team Okta’s Enterprise Data & Insights team empowers data-driven decision making across the company by delivering trusted analytics, insights, and tools. We partner closely with teams such as Marketing, Sales, Finance, Product, and Customer First to unlock business value through data strategy, scalable solutions, and impactful storytelling. The Staff Data Analyst Opportunity We are looking for a Staff Data Analyst who has a passion for driving decisions and insights through data to join the Enterprise Data & Insights team. You will be successful if you are detail-oriented, analytical, like solving big problems, connecting dots, understanding business challenges and determining options to solve using data, and can effectively communicate with team members and business partners. In this role, you will be key in creating the foundation for data-based decision-making across Okta's functional business teams and will work with internal customers to identify ways to effectively leverage data using cutting edge cloud and big data technologies to drive business insights. What you’ll be doing Serve as the definitive SME for Customer First analytics, defining the data models, metrics, and value drivers that steer company strategy. Lead the exploration and integration of AI-driven tools to automate workflows and pioneer new methodologies for data discovery, including defining the foundational semantic models that power our AI agents. Architect the analytics strategy for customer insights, leveraging product telemetry and public data to identify and predict risk and growth signals. Own the vision for our semantic layer, ensuring it supports advanced modeling, self-service, and high-integrity dashboarding. Participate in high-impact initiatives in predictive modeling (cross-sell, churn, LTV) that directly influence GTM execution. Partner with leadership and account teams to translate raw insights into a high-impact, action oriented Command Center, empowering account teams to instantly prioritize and execute on the most urgent opportunities and risks. Partner with Engineering to co-design data pipelines and transformations that ensure long-term scalability and data quality. Set the bar for excellence in data storytelling and modeling, mentoring the broader team on best practices and process improvement. What you’ll bring to the role BS in CS, MIS, related technical degree 7+ years experience as a Data Analyst/Data Engineer/BI Developer Advanced SQL experience Excellent communication skills, both written and verbal, ability to work with all levels of the organization Provide thought leadership on the evolution of our analytics maturity, moving beyond traditional descriptive dashboards toward predictive, AI-enabled solutions that utilize NLP and deep analysis to drive proactive decision-making Experience with building reports and visualizations to represent data intuitively in Tableau or similar data visualization tools Advanced analytics, data science, AI/ML experience and techniques are a plus Ability to work cross-functionally and communicate with technical and non-technical teams Experience with ETL processes, software development, and lifecycle awareness, using Python, Java, Databricks, and Snowflake Excellent time management and prioritization skills What you can look forward to as an Okta employee! Amazing Benefits Making Social Impact Fostering Diversity, Equity, Inclusion and Belonging at Okta Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/. Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation. Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/. ir needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/. Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation. Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/. #LI-HM2 #LI-Hybrid P24716_3407508The annual base salary range for this position for candidates located in the San Francisco Bay area is between: $152,000—$190,000 USDBelow is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: https://rewards.okta.com/us. The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between:$136,000—$170,000 USDThe Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one.Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws.If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation.Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Personnel and Job Candidate Privacy Notice at https://www.okta.com/legal/personnel-policy/.

🏢 Summary: Senior Director, Data Platform and Engineering role leading a global data and analytics engineering team to build and scale a secure, AI-enabled data platform. Responsible for owning the end-to-end data lifecycle, strengthening governance and security, and delivering scalable data foundations that power AI/ML initiatives. Combines hands-on technical leadership with strategic oversight to ensure high-quality, trusted data across the organization. 🗂️ Requirements: 10+ years experience in data platform and data engineering, 5+ years in data engineering leadership role, Experience building data foundations for AI and ML initiatives, Deep knowledge of modern data stacks and data warehousing, Hands-on experience with ETL/ELT pipelines and data modeling, Proficiency in Python and SQL, Experience with cloud data platforms (AWS, GCP, or Azure), Experience implementing data governance and security controls, Experience supporting regulatory compliance (e.g., FedRamp), Proven experience leading and scaling data engineering teams 📃 Skills: Python, SQL, AWS, GCP, Azure, ETL, ELT, AI, ML, Tableau, FedRamp, Datawarehousing, Datamodeling, Governance 🏢 Description: Secure Every Identity, from AI to HumanIdentity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.The Technology, Data, and Intelligence Team Okta is the leading independent identity provider. The Technology, Data, and Intelligence (TDI) organization is the engine that powers Okta's global workforce, providing the technology and systems that enable our employees to do their best work. The Opportunity Okta is seeking a visionary and results-driven Senior Director, Data Platform and Engineering to lead a global data and analytic engineering team ensuring our data assets are leveraged to their full potential. Reporting to the VP of Data and Insights this role requires a leader who is as comfortable with a technical deep dive as they are with a strategic business discussion. You will be a "player-coach" who can build and mentor a world-class team while personally driving strategic initiatives and ensuring the integrity of our data foundation. A core part of your responsibility will be to champion and enable our AI strategy and technical foundations, ensuring that clean, trusted, and well-governed data is the foundation for all AI initiatives. With the growth of AI in our Products and our business, Okta’s data is more critical to our success than ever. This role will make sure we continue to support the organization run and grow, while building out the platform for the future. Candidates should be energized by that challenge. What You'll Do Lead and Inspire a High-Performing Team: Build, mentor, and scale a diverse, high-performing team of data and analytics engineers, fostering a culture of excellence, collaboration, and continuous learning. Champion AI Enablement: Act as a critical partner to the AI Engineering teams. Ensure our data and data infrastructure and practices are optimized to support and accelerate AI development and deployment. This includes defining data governance standards, building high-quality training datasets, and developing scalable data pipelines for AI/ML models. Advance the Data Foundation: Own “back end” data lifecycle for critical business domains, from data ingestion and ETL/ELT pipelines to data modeling, quality assurance, and governance. Ensure a single source of truth for key metrics across the organization. Enhance Data Security and Governance: Partner with Security leaders to define and implement policies and systems to safeguard data privacy, ensure regulatory compliance, and protect sensitive information. This includes establishing robust data access controls, audit trails, and data retention policies. Partner Cross-Functionally: Collaborate closely with technology and business partners, including Product and Engineering leadership, to embed data and analytics into both internal and customer facing product development. What You Bring Experience: 10+ years of progressive experience in data platform, and data engineering, with at least 5+ years in a leadership role. AI Know How: Demonstrated experience in building data foundations and pipelines specifically to support and accelerate AI and machine learning initiatives. Technical Expertise: Deep knowledge of modern data stacks, including data warehousing, ETL/ELT pipelines, data modeling, and Tableau. Proficiency with Python, SQL, and experience with cloud-based data environments that enable AI use-cases (e.g., AWS, GCP, Azure). Governance: Proven ability to build secure solutions for both commercial and public sectors. Experience with FedRamp and the public sector cloud strongly preferred. Cross-Functional Collaboration: Exceptional ability to translate technical needs across product and IT platforms. Must also have the ability to communicate complex data concepts to both technical and non-technical audiences. Team Development: A track record of successfully hiring, mentoring, and leading high-performing data teams. Problem-Solving: A strategic mindset and a passion for solving ambiguous, complex business problems with a rigorous, data-driven approach. #LI-MC1 #LI-Hybrid #P14112_3419375The annual base salary range for this position for candidates located in the San Francisco Bay area is between: $276,000—$379,500 USDBelow is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: https://rewards.okta.com/us. The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between:$246,000—$338,800 USDThe Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one.Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws.If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation.Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Personnel and Job Candidate Privacy Notice at https://www.okta.com/legal/personnel-policy/.

🏢 Summary: Senior Manager role leading multiple engineering teams responsible for building and operating a resilient, high-performance data streaming backbone across a multi-cloud environment. The position focuses on defining strategy, ensuring uptime and reliability, and driving engineering excellence for large-scale distributed authentication and authorization services. It combines technical leadership with ownership of roadmap execution and operational robustness. 🗂️ Requirements: Proven experience leading multiple engineering teams, Experience coaching senior engineers and engineering managers, Strong background in scalable distributed systems, Experience with multi-cloud environments, Ownership of service reliability and uptime, Experience defining technical roadmaps in Agile environments, Ability to lead incident response for complex systems, Strong architectural and technical decision-making skills 📃 Skills: AWS, Azure, Kafka, Kubernetes, Docker, PostgreSQL, MongoDB, Go, Java, Node.js, Datadog, IAM, Agile, Observability, DistributedSystems 🏢 Description: Secure Every Identity, from AI to HumanIdentity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Opportunity Auth0’s platform is the front door for thousands of customers and millions of users. On the Platform Engineering team, we build the resilient foundations that enable customers to rely on Auth0 for always-on authentication and authorization services. As the Senior Manager of Data Streaming Services, you will lead the evolution of our streaming data backbone across a multi-cloud footprint. You will oversee multiple engineering teams dedicated to making data streaming seamless, reliable, and high-performance. This is a "manager of managers" role requiring a blend of strategic foresight, execution rigor, and technical grit. You will set the vision for our streaming services, mentor high-performing teams, and take accountability for our service uptime guarantees. What you’ll achieve Lead a world-class team of teams. Oversee data streaming infrastructure and services that power our global platform across AWS and Azure. Own roadmap and execution. Partner with product and stakeholder teams to define the team's strategy and prioritized roadmap. Drive engineering excellence. Set high standards of quality, reliability, and operational robustness, championing best practices in software development, from code reviews to observability and incident management. Lead an automation-first culture. Reduce operational friction and ensure infrastructure is self-healing and code-defined. Draw efficiency from AI-assisted development. Act as a technical leader. Lead response on incidents for services under ownership and help teams navigate complex distributed systems failures. What you’ll bring Proven engineering leadership, building and leading teams of teams. Experience coaching Staff+ engineers and engineering managers. Strong technical and architectural acumen. Background in building scalable, distributed systems. Comfortable participating in and guiding technical discussions. Strong project management skills. Expertise in creating technical roadmaps, prioritizing effectively in an agile environment, and managing complex project dependencies. Collaborative leadership style, adapted to remote ways of working. Excellent written and verbal communication skills to build strong relationships with stakeholders and inspire others. Bonus Points Experience developing data-intensive applications in a modern programming language such as go, node.js, or Java. Experience with databases such as PostgreSQL and MongoDB. Experience with distributed streaming platforms like Kafka. Familiarity with concepts in the IAM (Identity and Access Management) domain. Experience with cloud providers (AWS, Azure), container technologies such as Kubernetes and Docker, and observability tools such as Datadog. Experience building reliable, high-availability platforms for enterprise SaaS applications. We do not expect you to be an expert in all of the above, only that you can learn the less familiar fast. #LI-Hybrid P15407_3389736Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: https://rewards.okta.com/us. The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between:$207,000—$284,000 USDThe Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one.Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws.If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation.Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Personnel and Job Candidate Privacy Notice at https://www.okta.com/legal/personnel-policy/.