2 Backend Java Engineers

🏢 Summary: Hands-on data infrastructure engineering role focused on large-scale pipeline migrations and evolution of the company’s data processing stack. The position involves contributing to platform development across Flink and Lakehouse architectures while ensuring performance, reliability, and cost efficiency. High-impact role embedded in a data engineering team delivering production-grade data platforms. 🗂️ Requirements: Strong Java development experience, Experience with JVM-based data processing framework, Experience with Flink, Beam, Dataflow or Spark, Proficiency in SQL, Experience with BigQuery, Experience with cloud infrastructure, Experience with containerized applications, Knowledge of Kubernetes basics, Experience with Scala or Python for data pipelines, Experience working with production data engineering systems 📃 Skills: Java, Flink, Beam, Dataflow, Spark, SQL, BigQuery, Kubernetes, Scala, Python, JVM, DevOps, Lakehouse, Cloud 🏢 Description: The Data Infrastructure PA enables the company to solve complex and critical data engineering problems by providing platforms and tooling for the production, management, and consumption of high-quality data. We're looking for an engineer to support hands-on implementation and migration work as we evolve our data processing stack. This is a high impact and execution-focused engagement — you'll be contributing to company wide migration efforts and platform development. What You'll Work On You'll be embedded in a team in Data Infrastructure PA, contributing to hands-on engineering work. This includes large-scale pipeline migrations — validating performance and cost outcomes and helping move workloads to our evolving stack — as well as contributing to platform development across our Flink platform, Lakehouse architecture and beyond, as our priorities evolve. What We're Looking For You have solid, hands-on experience in backend engineering and are comfortable jumping into an existing platform codebase and making meaningful contributions quickly. Specifically: Strong Java development skills, with experience in data platform or data engineering contexts Practical experience with at least one JVM-based data processing framework — Flink experience is a plus; Beam, Dataflow, or Spark also relevant Comfortable with SQL and cloud data analytics platforms, particularly BigQuery DevOps is part of your day-to-day: you work with cloud infrastructure, containerised applications, and are familiar with Kubernetes basics Experience working with data engineering pipelines in Scala and/or Python You write quality code and understand what it means to ship reliably in a production environment You can work autonomously in an ambiguous environment and move quickly without waiting to be directed Nice to Have Prior experience with large-scale pipeline migrations Familiarity with cost optimisation in cloud data processing workloads Job Posting Start Date:   2026-05-18 Job Posting End Date:   2026-11-27

🏢 Summary: Design and build a modern Data Platform from scratch for an insurance client, establishing a governed, production-ready Snowflake environment and enabling AI capabilities. The role covers full lifecycle ownership from architecture and data modelling to pipeline implementation and post-launch operations. You will develop scalable data ingestion and processing solutions while promoting best practices, automation, and CI/CD standards. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (Snowflake, BigQuery or Redshift), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design, Experience with cloud platforms (AWS, GCP or Azure), Experience with cloud data services (S3, GCS, ABS, EMR, Dataproc, MWAA, Composer, ADF or AWS Glue), Ability to design and maintain data quality and governance standards, Experience working in Agile environments 📃 Skills: Python, SQL, Snowflake, Databricks, BigQuery, Redshift, Azure, AWS, GCP, Terraform, dbt, Spark, PowerBI, ADF, Glue, EMR, Dataproc, MWAA, Composer 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project JetBrains Projectt scope The client is introducing Atlan as a new internal Data Catalogue solution and uses Glean as a company-wide unified search platform for thousands of employees. To ensure a smooth transition from our existing Knowledge Base and OpenMetadata setup, we need to index Atlan assets into Glean so that metadata for databases, tables, metrics, and reports is easily discoverable through search. Tech stack Python,  System & Data Integration, Kubernetes, System design, Infrastructure mindset Skills We’re looking for a Data Platform Engineer with experience in data platforms and system design at scale. We expect a track record in designing integration architectures for external systems and streamlining data migration/ingestion. As a Data Platform Engineer, you will design and implement a solution that: Periodically indexes Atlan metadata assets into Glean, runs on a configurable schedule (hourly/daily), is production-ready, observable, and maintainable by our DevOps team after handover. Moreover, ensure compliance and data governance at the appropriate level in line with the company’s standards. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more! Apply now

🏢 Summary: Design and build a modern data platform from scratch for an insurance client, covering architecture, data ingestion, modelling, and production operations. The role focuses on establishing a governed, scalable Snowflake-based environment to enable reliable reporting and AI capabilities. You will take ownership across the full data lifecycle, from requirements definition to deployment and maintenance. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (BigQuery, Redshift or Snowflake), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design and maintenance, Experience with AWS, GCP or Azure cloud services, Ability to design and build data ingestion and processing pipelines, Experience working in Agile environment, Understanding of data governance and data quality concepts 📃 Skills: Python, SQL, Snowflake, BigQuery, Redshift, Databricks, Azure, AWS, GCP, Terraform, dbt, PowerBI, Spark, ETL, CI/CD 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project Data Foundation & AI Enablement Project Scope We are architecting a modern Data Platform for a fast-scaling client in the Insurance sector. Our work consolidates fragmented legacy systems, organises data from a vast number of sources, and establishes a standardised, governed, and future-proof data foundation. We aim to unlock the full value of the company’s data, enabling faster, informed decision-making and providing the backbone for business growth and AI readiness. Tech stack SQL, Python, Snowflake, dbt, Data modelling, Data quality, Power BI, Azure, Terraform Challenges The primary objective is to deliver a robust data foundation and enable AI capabilities for a client that has grown organically. The work focuses on several key areas: Establishing a production-ready, fully operational Snowflake environment and driving operational excellence. Translating complex business logic into accurate data models to ensure the platform truly reflects business reality. Integrating diverse data sources to build reliable data products and comprehensive data dictionaries. Managing the full Data Engineering and Data Science lifecycle to support production ML and AI experimentation. Taking ownership from concept to deployment. Cultivating an engineering mindset by promoting automation, CI/CD, and rigorous standards. Team We are building a small (4-6 people), agile, cross-functional team capable of delivering the complete data platform, from initial architecture to production operations. Roles involved: DevOps, Data Engineer, Snowflake Specialist, MLOps/AI Engineer, Business Analyst (BA). The team will collaborate closely with business stakeholders to ensure effective knowledge transfer and strict alignment with strategic goals. Team The team is small but highly motivated, taking on a broad scope of responsibilities as the platform is built and expanded. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more! Apply now

🏢 Summary: Build and scale a central policy repository and web-based management tooling that powers content detection, enforcement, and compliance systems. The role combines backend API development, data pipeline engineering, and frontend application development to support policy versioning and regulatory requirements at scale. You will collaborate across safety, legal, and compliance teams to deliver reliable, user-friendly internal tools. 🗂️ Requirements: Experience building and operating backend services and APIs in production at scale, Proficiency in Java, Kotlin, Go or similar backend language, Experience building web frontends with React, TypeScript or similar framework, Understanding of API design, schema evolution and backward compatibility, Experience with data pipelines, real-time and batch processing, Ability to design and build user-friendly interfaces, Experience working in regulated or compliance-sensitive environments, Ability to collaborate across teams and communicate with non-technical stakeholders 📃 Skills: Java, Kotlin, Go, React, TypeScript, APIs, Data, Pipelines, Real-time, Batch 🏢 Description: About the Team We design the consumer experience end-to-end, across every screen, platform, and partner integration. Our goal is to make listening feel effortless, personal, and joyful for hundreds of millions of users around the world. The Policy & Safety group builds the infrastructure that keeps that experience safe at scale. This includes the rule engines, enforcement pipelines, policy configuration systems, and compliance data platforms behind content moderation. We work at the intersection of backend platform engineering, machine learning systems, and regulatory compliance, partnering closely with trust and safety, legal, and content protection teams. Because we sit on the path of every new content type and feature, our work makes safety a default part of the company experience while supporting global regulatory requirements and ongoing product innovation. The Policy Catalog team owns the central policy repository, the single source of truth for how content policies are defined, versioned, and used across detection, enforcement, and compliance. We are building and scaling this system to be the reliable foundation that the entire safety enforcement chain depends on, bringing policies from many areas of the business into one well-structured system. A core part of this work is building the web-based tooling that lets teams manage the policy registry directly, ensuring our systems are as strong on the frontend as they are on the backend. What You'll Do You will build and maintain the APIs and services that expose policy logic consistently across detection, enforcement, and compliance surfaces. You will contribute to the design and development of the central policy repository, expanding its capabilities to cover new use cases including detection, and build data pipelines that feed structured policy data into downstream machine learning models and enforcement systems. Develop and maintain backend services and APIs. Design and implement the internal web application for policy management by non-technical stakeholders. Ensure the full experience is responsive, reliable, and user-friendly. Ingest, structure, version, and ensure the reliability of policies across the business. Collaborate with detection, enforcement, and compliance partners to align on policy definitions. Translate regulatory and compliance requirements into engineering constraints. Write clean, well-tested, and well-documented code across the stack. Key Requirements Solid experience building and operating backend services and APIs in production at scale. Proficiency in a backend language such as Java, Kotlin, Go, or similar. Hands-on experience building web frontends with a modern framework such as React, TypeScript, or similar. Understanding of API design, schema evolution, and backward compatibility. Experience with data pipelines, real-time, and batch processing. Ability to build user-friendly interfaces that simplify complex workflows. Experience in regulated or compliance-sensitive environments. Effective collaboration across teams and clear communication with non-technical partners. Nice to Have Experience in developing internal tooling for non-technical audiences. Familiarity with data modeling for auditability, versioning, and querying. Other Details Start: ASAP/August - 6 months with possibility to extend Workplace: Stockholm, Sweden

🏢 Summary: Senior Backend Engineer role focused on building and scaling backend microservices for consumer-facing platforms and internal data privacy systems. The position involves developing distributed, event-driven systems supporting personalization, search, and regulatory compliance at scale. It requires strong experience in JVM technologies and cloud-native environments. 🗂️ Requirements: Strong commercial experience with JVM-based languages (Java or Scala), Experience with Kotlin or willingness to learn, Solid understanding of microservices architecture, Experience with event-driven systems, Experience with Docker and Kubernetes, Hands-on CI/CD experience in production, Experience with unit and integration testing, Experience with relational databases and SQL, Ability to design and maintain scalable distributed systems 📃 Skills: Java, Scala, Kotlin, JVM, Microservices, Docker, Kubernetes, CI/CD, SQL, PostgreSQL, AWS, Terraform, Elasticsearch, MongoDB, GraphQL, Go, Python 🏢 Description: We are looking for a Senior Backend Engineer to join a fast-growing product organization working on consumer-facing platforms and internal data systems. This role is suited for an experienced backend engineer who is comfortable building scalable, reliable services across different domains, from customer-facing journeys to data privacy and compliance infrastructure. About the Project: You will contribute to backend systems that power core customer experiences and internal platform initiatives. Depending on the team, this includes scaling a menu and personalization platform for high-traffic consumer applications, or building a centralized Data Privacy Service handling regulatory compliance (GDPR, CCPA) and Data Subject Requests at scale. Both streams require strong engineering fundamentals, a microservices mindset, and the ability to deliver in complex, distributed environments. Responsibilities: Design, develop, and maintain scalable backend microservices across consumer or data platform domains; Build systems supporting search, personalization, customer targeting, and engagement; Develop and operate services ensuring regulatory compliance and secure data handling (GDPR, CCPA); Work with event-driven architectures and distributed systems; Contribute to CI/CD pipelines, testing practices, and overall engineering quality; Collaborate with product and engineering teams to deliver reliable and performant solutions. Qualifications: Strong commercial experience with JVM-based languages (Java, Scala, or similar); Experience with Kotlin, or willingness to learn it on the project; Solid understanding of microservices architecture and event-driven systems; Experience with Docker and Kubernetes; Hands-on CI/CD experience in a production environment; Experience with unit and integration testing; Familiarity with relational databases (e.g. PostgreSQL) and SQL; AWS and Terraform experience is a plus; Experience with Elasticsearch, MongoDB, or GraphQL is a plus; Go or Python knowledge is a nice to have; Background in e-commerce, subscription platforms, or data privacy systems is a plus. Recruitment Process: Initial interview with our recruitment team; Interview with the hiring manager; Live Coding Assessment; Meeting with the Project Manager. Inuits Sp. z o.o. is registered in the National Register of Employment Agencies (KRAZ) under number 35420.

🏢 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: 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: Executive technical leadership role to scale and evolve a global AI-driven brand compliance platform built on cloud-native architecture. The position focuses on defining technical vision, overseeing scalable and resilient systems on GCP, and integrating AI/ML into production-grade products. The mission is to transform the engineering organization into a high-performance team while maintaining startup agility. 🗂️ Requirements: Proven experience as CTO, VP Engineering, or Head of Tech in startup environment, Expert knowledge of Java, Python, and React, Strong experience with cloud-native architectures on GCP, Experience building data-intensive platforms, Experience integrating AI/ML into production systems, Experience designing scalable microservices architectures, Experience with event-driven systems, Ability to define and execute technical strategy, Experience leading and scaling cross-functional engineering teams 📃 Skills: Java, Python, React, GCP, Microservices, GraphQL, AI, ML, NLP, DevOps, QA, Cloud, Architecture, Event-driven 🏢 Description: What’s at stake? We’re changing the rules of the game in global brand compliance. Our product is in an extremely dynamic phase of development, and the largest e-commerce platforms on the market are already taking a direct interest in our innovative approach. What gives us a massive advantage is access to unique datasets—powerful fuel for building advanced AI-based solutions. We’re looking for a leader who will step up and take our product to the very top! Your mission and challenge : We need a technological visionary who will take the helm and transform our product and engineering organization into a high-performance machine. You must know how to scale processes and architecture without losing the agility and startup spirit that drives us. Our Tech Stack We build on a robust and modern foundation: Backend: Java (modern frameworks, microservices architecture). Frontend: React (building intuitive, data-rich management dashboards). AI/ML Module: Python (dedicated models for natural language processing of regulations and automated decision-making). Infrastructure: Google Cloud Platform (GCP). Engineering Philosophy: High focus on "Compliance by Design," high availability, and seamless integration with global regulatory data sources. Key Responsibilities Technical Strategy: Define the long-term technical vision and roadmap, ensuring the platform remains "right by design" and scalable for global markets. Architecture Oversight: Oversee the evolution of the GCP and Event-driven infrastructure, ensuring high resilience and security. Team Leadership: Scale and mentor a cross-functional engineering team (Software, Data, AI, DevOps, QA), fostering a culture of high velocity and low ego. Product-Tech Alignment: Collaborate with stakeholders to translate complex burdens into elegant, automated digital products. Innovation: Drive the integration of AI/ML and GraphQL layers. Requirements Leadership: Proven experience in executive technical leadership (CTO, VP Engineering, or Head of Tech) in a fast-paced startup environment. Deep Technical Roots: Expert knowledge of modern stacks (java, python, react) and cloud-native architectures (GCP). Data & AI Vision: Experience building data-heavy platforms and integrating AI/ML into production workflows. Business Acumen: Ability to align technical decisions with commercial goals and regulatory requirements. Mindset: A pragmatic leader who stays "close to the code," values ownership, and thrives on solving high-impact problems.

🏢 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: Remote role focused on building scalable data pipelines and AI-driven solutions for datacenter development planning systems. The position involves integrating multiple data sources, configuring AI agents, and delivering BI-ready outputs while collaborating directly with clients. It offers high autonomy and ownership across the full software development lifecycle. 🗂️ Requirements: 4+ years software development experience across full SDLC, 3+ years hands-on experience with Java, Strong SQL skills, Experience working with databases, Practical experience developing or configuring AI Agents, Experience in system integration, Client-facing communication experience in English, Ability to design and implement architecture solutions 📃 Skills: Java, SQL, Databases, AI, ETL, GCP, Python, BI 🏢 Description: Are you passionate about building scalable, high-performance platforms that power the next generation of data-driven applications? Join our dynamic team working on mission-critical software systems for Datacenter development planning - all in a fully remote work environment . We manage complex supply timelines and supplier relationships, delivering solutions that make a real impact for our clients. If you thrive in a modern, autonomous engineering environment and enjoy direct collaboration with stakeholders, we want to hear from you! If you're ready to make an impact in a dynamic environment, we want to hear from you! Responsibilities Build robust data pipelines integrating information from multiple data sources Configure and develop AI Agents to process and analyze data efficiently Transform and optimize agent outputs into BI-friendly formats for business intelligence use Communicate directly with clients on a daily basis to gather requirements and provide updates Propose and implement design and architecture solutions for your deliverables Collaborate with world-class engineers, architects, and product managers Focus on development activities in an environment with minimal meetings and high autonomy Requirements 4+ years of experience in software development and integration across the full system implementation lifecycle (analyze, design, implement, build, test, support) 3+ years of hands-on experience with Java Strong SQL skills and experience working with databases Practical experience in developing or configuring AI Agents Excellent English communication skills, with proven experience in client-facing roles Strong self-management and prioritization abilities Nice to have Experience with Google Cloud Platform (GCP) Python programming skills ETL (Extract, Transform, Load) experience Familiarity with Agent Development Kit We offer/Benefits We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.