Data Engineer

🏢 Summary: Founding Technical Recruiter role focused on building and scaling the full-cycle recruiting function for technical teams including AI/ML, Engineering, Data, and Design. The position involves sourcing senior technical talent, partnering with leadership on hiring strategy, and creating recruiting processes and infrastructure for a fast-growing AI company. 🗂️ Requirements: 4+ years of full-cycle technical recruiting experience, Experience recruiting for senior and staff-level engineering roles, Strong sourcing experience for hard-to-fill technical positions, Experience in a fast-growing product-led startup, Ability to use recruiting metrics and pipeline data, Experience building recruiting processes and interview frameworks, Ability to work autonomously and manage end-to-end searches, Willingness to work in person in SF or NYC office 📃 Skills: Recruiting, Sourcing, ATS, AI, ML, Data, Engineering, Analytics 🏢 Description: Stuut is transforming accounts receivable for B2B companies—making collections smarter and faster for companies that have historically relied on manual processes that are labor intensive and costly. Our platform is gaining traction with finance teams across industrials, chemicals, and manufacturing sectors from Fortune 10 brands to scaling midmarkets. We're backed by top-tier investors including a16z, Khosla, Activant, 1984 Ventures and Page One.The RoleWe're hiring our first dedicated recruiter. Nearly every open role at Stuut today is technical—AI/ML, voice infrastructure, applied AI engineering, data, and design—and the pace of hiring is only accelerating. As our Founding Technical Recruiter, you'll own the full recruiting lifecycle for these roles, from sourcing through offer, and build the talent function itself: the processes, tooling, employer brand, and hiring standards that will carry us through the next several years of growth.You'll report directly to the CEO and partner day-to-day with engineering and product leadership. This is not a role where you inherit a playbook—you'll write it. If you're energized by owning searches end-to-end for senior technical talent, being measured on the quality of the people you bring in, and shaping how a fast-moving AI company scales its team, this is the seat.What You'll DoOwn full-cycle recruiting for technical roles: run searches end-to-end across Engineering, AI/ML, Data, and Design—from kickoff and sourcing through interviews, references, and closed offers.Source proactively and creatively: build pipelines of exceptional senior+ engineers and researchers through outbound, referrals, communities, events, and channels other recruiters haven't thought of yet. Top candidates here won't come inbound—you'll go find them.Partner with leadership as a trusted advisor: work directly with the CEO and hiring managers to define role scope, success profiles, and evaluation criteria—and be a consistent voice for quality throughout the process.Build the recruiting function from scratch: stand up our processes, interview frameworks, scorecards, and ATS hygiene; establish the metrics and reporting that keep hiring fast and honest.Deliver an exceptional candidate experience: every candidate—hired or not—should leave the process thinking more of Stuut than when they entered it.Champion Stuut's story in the market: represent our product, traction, and technical bar to passive candidates and position Stuut as the place ambitious engineers want to build.Use data to get better every week: track pass-through rates, diagnose bottlenecks, and iterate on sourcing and process based on what the numbers tell you.You Might Be a Fit If You…Have 4+ years of full-cycle recruiting experience with a focus on technical roles, ideally in-house at a fast-growing, product-led startup.Have owned searches for senior and staff+ engineering talent and can establish instant credibility with technical leaders and candidates.Have strong sourcing chops—you're comfortable building pipelines for hard-to-fill roles rather than waiting on inbound.Have worked somewhere with a very high talent bar and understand the subtle indicators that separate good from great technical talent.Are data-driven: you use pipeline metrics to prioritize your time, spot problems early, and make the case for change.Operate with autonomy—you're used to leading searches end-to-end and prioritizing your own workload without direction.Are excited to build a function, not just fill seats: processes, employer brand, and hiring infrastructure that scale.Want to work in person, at speed, alongside the founders in our SF or NYC office.CompensationTop-of-market salary and equity packageBenefits (for U.S.-based full-time employees)Medical, dental & vision insurance coverage for you401(k) & MatchEquityFlexible PTOParental LeaveCompensationTop-of-market salary and equity packageBenefits (for U.S.-based full-time employees)Medical, dental & vision insurance coverage for you401(k) & MatchEquityFlexible PTOParental LeaveCompensation Range: $180K - $250K

🏢 Summary: High-impact full stack Applied AI role focused on designing, building, and scaling end-to-end systems for a B2B financial operations platform. You will own projects from architecture to production, delivering scalable backend services and modern frontend experiences while collaborating closely with cross-functional teams and customers. The role combines deep technical execution with system design, cloud infrastructure, and engineering leadership in a fast-growing startup environment. 🗂️ Requirements: 5+ years full stack engineering experience, Strong proficiency in Python, Strong proficiency in TypeScript, Experience building scalable backend services, Experience building modern frontend applications, Expertise in database design, Expertise in API development, Strong system architecture knowledge, Experience with modern frontend frameworks (Vue.js, React, or Angular), Experience with backend frameworks (Django, FastAPI, Flask, or Node.js), Hands-on experience with cloud platforms, Experience with containerization, Experience with CI/CD pipelines, Ability to lead complex cross-stack projects, Experience mentoring engineers 📃 Skills: Python, TypeScript, Vue, React, Angular, Django, FastAPI, Flask, Node.js, AWS, GCP, Azure, CI/CD, APIs, Microservices, SQL, Containers 🏢 Description: Stuut is transforming accounts receivable for B2B companies, making collections smarter and faster for organizations that have historically relied on manual, labor-intensive processes. The platform is used by finance teams across industrials, chemicals, and manufacturing sectors, from Fortune 10 brands to scaling midmarkets. The Role We’re hiring a Member of Technical Staff – Applied AI, Fullstack to design, build, and scale end-to-end systems that power Stuut’s platform for B2B financial operations. You’ll work closely with Product, Design, Backend, and Frontend teams, as well as customers, to deliver seamless, high-performance experiences across the entire stack. This is a high-impact role for someone who can own projects from inception through scaling, think across systems, and deliver reliable, user-centered solutions. You’ll play a critical role in shaping engineering culture and product experience, ensuring full stack systems are elegant and scalable. What You’ll Do - Drive the full stack technical vision through cross-functional collaboration across product, design, and engineering. - Lead complex projects spanning frontend, backend, and system integrations, from API design to polished user experiences. - Build end-to-end features from database schema to production-ready UI, ensuring seamless data flow, scalability, and performance. - Design and implement robust backend services, APIs, and microservices while crafting intuitive, responsive frontend experiences. - Continuously improve engineering processes, tools, and systems to scale productivity, reliability, and velocity. - Recruit, mentor, and develop engineering talent, fostering a culture of excellence, humility, and speed. - Engage directly with customers to understand and solve complex workflow challenges. You Might Be a Fit If You… - Have 5+ years of full stack engineering experience with a track record of delivering products at scale. - Are highly skilled in Python and TypeScript, with experience building robust backend services and modern frontend applications. - Have strong expertise in database design, API development, and system architecture. - Are proficient in modern frontend frameworks like Vue.js, React, or Angular and backend frameworks such as Django, FastAPI, Flask, or Node.js. - Have hands-on experience with cloud platforms (AWS, GCP, Azure), containerization, and CI/CD pipelines. - Thrive in early-stage startup environments and enjoy building systems and processes from scratch. - Enjoy engaging directly with customers to shape technical solutions. - Have experience mentoring engineers and shaping high-performing engineering cultures. - Are committed to continuous learning and solving customer pain points through scalable solutions. Compensation Top-of-market salary and equity package Benefits (for U.S.-based full-time employees) - Medical, dental & vision insurance coverage - 401(k) & match - Equity - Flexible PTO - Parental leave Compensation Range: $185K - $250K

🏢 Summary: Senior Product Designer role focused on building AI-driven and automated UX workflows for B2B accounts receivable software. The position involves collaborating with product, engineering, and customers to design enterprise-grade interfaces and scalable design systems in a fast-moving startup environment. 🗂️ Requirements: 5+ years of B2B product design experience, Experience in SaaS or enterprise software, Strong enterprise UX expertise, Experience with workflow automation, Experience designing AI-driven interfaces, Ability to design prompt-based user experiences, Proficiency with AI tooling for prototyping, Technical fluency with engineering collaboration, Portfolio focused on UX/UI for B2B and AI products, Experience with Figma, Experience with prototyping tools, Knowledge of user research methodologies, Ability to work in a startup environment 📃 Skills: Figma, UX, UI, SaaS, AI, Automation, Prototyping, Research 🏢 Description: Stuut is transforming accounts receivable for B2B companies by making collections smarter and faster through AI-driven automation. About the Role As a Senior Product Designer, you’ll play a critical role in shaping the user experience, designing interfaces that feel intelligent, agentic, and seamless for customers. You’ll collaborate closely with engineering, product, and customers to craft intuitive workflows that leverage AI and automation. What You’ll Do - Design experiences that are instantly familiar to customers and set the bar for agentic UX and financial workflows - Own customer outcomes by identifying opportunities, testing solutions with customers, and partnering with product and engineering teams through release and beyond - Think in systems and balance long-term vision with speed and iteration - Design patterns and modules that increase shipping velocity and customer familiarity - Seek alignment early using prototypes, data, and customer feedback What We’re Looking For - 5+ years of experience in B2B product design, preferably in SaaS or enterprise software - Strong background in enterprise UX, workflow automation, and AI-driven interfaces - Experience designing prompt-based or AI-powered user experiences - Ability to use AI tooling to prototype projects - Technical fluency and comfort working with engineering teams on complex, data-driven products - Portfolio showcasing UX/UI work focused on B2B, automation, and AI-driven interfaces - Experience with Figma, prototyping tools, and user research methodologies - Self-starter mentality and comfort working in a fast-moving startup environment Compensation - Top-of-market salary and equity package Benefits - Medical, dental, and vision insurance coverage - 401(k) with match - Equity - Flexible PTO - Parental leave Compensation Range: $220K - $290K

🏢 Summary: Design and deploy production-grade voice and audio AI systems for enterprise finance workflows, building real-time voice agents and speech-driven automations. The role focuses on fine-tuning speech and multimodal models, engineering scalable low-latency AI pipelines, and integrating conversational AI into a SaaS platform. You will translate cutting-edge audio and LLM research into reliable, measurable business impact for B2B financial operations. 🗂️ Requirements: 5+ years software engineering experience, 2+ years experience in applied AI/ML, speech, or audio systems in production, Experience building and shipping voice, audio, or conversational AI systems, Experience with speech-to-text, text-to-speech, audio processing, or multimodal models, Experience integrating and fine-tuning LLMs for conversational or agent-based systems, Knowledge of LLMOps/MLOps practices including deployment, monitoring, evaluation, and A/B testing, Proficiency in Python, Experience with PyTorch, TensorFlow, Transformers, or audio ML frameworks, Experience building real-time or low-latency systems, Experience integrating AI systems into enterprise or SaaS platforms 📃 Skills: Python, PyTorch, TensorFlow, Transformers, LLMs, Speech-to-text, Text-to-speech, Audio, Multimodal, MLOps, LLMOps, A/B testing, Streaming, SaaS 🏢 Description: The Role We’re hiring a Member of Technical Staff – Audio and Voice AI Systems to design, build, and deploy AI-powered voice and audio systems that solve real-world financial operations challenges. You’ll take state-of-the-art research in speech, audio, and multimodal AI and translate it into production-grade, real-time voice experiences that deliver measurable customer impact. From intelligent voice agents that interact with customers to audio-driven workflow automation and speech-based data extraction, you’ll create scalable, reliable AI systems that integrate seamlessly into the platform. Your work will directly shape how finance teams and their customers interact through voice. This is a hands-on role for an engineer who thrives at the intersection of audio AI, real-time systems, and practical business impact—turning cutting-edge models into trusted, delightful voice experiences for enterprise finance workflows. What You’ll Do - Build & Deploy Voice AI Systems: design and ship production-ready audio and voice-based AI features, including real-time voice agents and speech-driven workflows. - Craft High-Quality Voice UX: use modern speech-to-text, text-to-speech, and conversational AI platforms to create natural, responsive, and emotionally aware voice experiences tailored to financial use cases. - Adapt & Fine-Tune Audio and Multimodal Models: fine-tune and optimize speech, audio, and LLM-based models for accuracy, latency, and reliability in real-world environments. - Engineer Real-Time, Scalable AI Pipelines: build end-to-end AI/ML pipelines spanning audio ingestion, streaming inference, orchestration, and monitoring with enterprise-grade availability and performance. - Establish Evaluation & Monitoring Frameworks (LLMOps): design rigorous evaluation systems to measure quality, latency, accuracy, drift, and business outcomes for voice and text-based AI systems. - Automate Financial Workflows via Voice: develop AI-powered voice automations that reduce manual effort in collections, reconciliation, and customer communication. - Collaborate Cross-Functionally: partner with Product, Engineering, Design, and customers to translate business needs into effective, user-centered voice AI solutions. - Measure & Communicate Impact: define success metrics and continuously improve AI systems based on real-world usage and customer feedback. You Might Be a Fit If You… - Have 5+ years of software engineering experience, with 2+ years focused on applied AI/ML, speech, or audio systems in production. - Have built and shipped voice, audio, or conversational AI systems used by real customers. - Have experience with speech-to-text, text-to-speech, audio processing, or multimodal models. - Have integrated and fine-tuned LLMs for conversational or agent-based systems. - Understand LLMOps / MLOps best practices, including deployment pipelines, monitoring, evaluation, and A/B testing. - Are fluent in Python and experienced with PyTorch, TensorFlow, Transformers, or audio ML frameworks. - Have built real-time or low-latency systems and understand the tradeoffs involved. - Can translate business and UX requirements into robust, scalable AI solutions. - Have experience integrating AI systems into existing enterprise or SaaS platforms. - Enjoy working on ambiguous problems where product definition, UX, and engineering meet. Compensation Top-of-market salary and equity package Benefits (for U.S.-based full-time employees) - Medical, dental & vision insurance coverage - 401(k) & Match - Equity - Flexible PTO - Parental Leave Compensation Range: $220K - $320K

🏢 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: Staff Data Scientist (Tech Lead) role focused on building and scaling real-time AI-driven decisioning systems to improve product conversion. The position combines hands-on machine learning leadership with technical ownership of production ML pipelines and experimentation strategy. You will drive advanced ML initiatives including recommendation systems, uplift modeling, and LLM-based personalization in low-latency environments. 🗂️ Requirements: 10+ years experience in Data Science with production ML systems, Expert-level Python and SQL, Strong experience with PySpark or Apache Spark, Experience building real-time ML systems with strict latency constraints, Proven experience with gradient boosting and recommendation systems, Strong background in A/B testing and causal inference, Experience building ML pipelines on AWS, Hands-on experience with LLMs including fine-tuning and evaluation, Experience with feature engineering and model monitoring in production 📃 Skills: Python, SQL, PySpark, Spark, NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, AWS, Databricks, LLMs, NLP, Clustering, Uplift, Bandits, ABTesting, CausalInference 🏢 Description: We are looking for a Staff Data Scientist to join a Growth Alliance team at the Tech Lead level. This role goes beyond hands-on data science, it requires a candidate who can set technical direction, lead complex ML initiatives, and act as a strategic partner to business stakeholders. You will operate at the intersection of advanced machine learning, real-time systems, and product growth. About the Project: This is a Staff / Tech Lead position within a team driving AI-powered decisioning at scale. You will work on systems with strict real-time constraints (<40 ms latency) that directly impact end-user experience and conversion. The mission is to move the product toward AI-driven decisioning, targeting a measurable improvement in conversion (~5%). You will be expected to challenge assumptions, define the technical roadmap, and ensure that ML systems perform reliably in production. Responsibilities: Lead the design and implementation of production ML systems, including real-time decisioning and personalization engines; Drive adoption of contextual bandits, uplift modeling, and advanced recommendation frameworks; Define experimentation strategy including A/B testing, causal inference, and synthetic controls; Oversee feature engineering at scale and ensure robust model monitoring and validation practices; Act as a technical owner for decisioning platforms and Martech integrations; Collaborate with and influence senior business stakeholders to shape data science strategy; Guide and mentor other data scientists on the team; Lead GenAI and LLM-based initiatives including fine-tuning, evaluation, and content personalization. Qualifications: 10+ years of experience in Data Science, with a strong track record in production ML systems; Expert-level Python (NumPy, Pandas, Scikit-learn) and SQL; Deep experience with PySpark / Apache Spark for large-scale data processing; Mastery of gradient boosting methods (XGBoost, LightGBM), recommendation systems, NLP, clustering, and uplift modeling; Extensive experience with A/B testing, causal inference, statistical modeling, and synthetic controls; Proven ability to build and maintain production ML pipelines on cloud platforms (AWS preferred); Experience with decisioning platforms, personalization engines, and Martech integrations; Hands-on experience with LLMs, prompt engineering, evaluation, and fine-tuning; Strong stakeholder management skills with the ability to challenge assumptions and ask the right questions; Databricks experience is a nice to have. 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 offer is for a Software Engineer (Data) role focused on building scalable data infrastructure and production-ready ML systems within an AI-driven environment. The position combines backend engineering, data engineering, and MLOps to design high-throughput pipelines and support AI solutions from experimentation to production. The role involves close collaboration with Data Science teams to shape architecture and engineering standards for next-generation data platforms. 🗂️ Requirements: 4+ years of software engineering experience, Strong proficiency in Python, Experience building scalable production systems, Experience with data-intensive applications and SQL databases, Knowledge of data modeling and query optimization, Experience with Terraform, Kubernetes, Docker or similar tools, Understanding of CI/CD pipelines and Infrastructure as Code, Experience implementing automated testing and clean architecture principles, Ability to productionize ML solutions with Data Science teams 📃 Skills: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker, Airflow, SQL, CI/CD, AWS, Snowflake, DBT, MLOps 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Data) to join our client’s growing AI and Data organization and help build the scalable foundations behind next-generation data and ML systems. In this role, you won’t just be working with data infrastructure; you’ll be shaping the software architecture, engineering standards, and production-ready platforms that power the company’s AI ecosystem. This is more than a traditional backend or data engineering position. You’ll work at the intersection of software engineering, data, and AI, partnering closely with Data Science and AI teams to bridge the gap between experimentation and production. From designing resilient systems to building scalable MLOps pipelines, your work will directly influence how AI solutions are developed, deployed, and scaled across the organization. Key takeaways: Stack: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Interview with Hiring Manager (45 min) Technical interview, live coding (1h) Cross-functional interview (1h) Responsibilities: Design, develop, and maintain scalable high-throughput data pipelines across complex data ecosystems. Build and optimize data models, schemas, and database structures to ensure long-term scalability and performance. Implement engineering best practices, including automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform). Partner closely with AI and Data Science teams to productionize machine learning solutions and develop scalable MLOps pipelines. Engineer and maintain feature stores and data infrastructure supporting AI-driven initiatives. Monitor, maintain, and improve the reliability and efficiency of containerized environments using Kubernetes, Docker, and Airflow. Ensure platform stability, observability, and operational excellence through proactive system monitoring and health checks. Collaborate cross-functionally with engineering and business stakeholders to translate complex technical concepts into actionable insights. Contribute to the architectural direction and scalability of the organization’s AI and data platforms. Drive the adoption of robust software engineering standards across data and infrastructure projects. Requirements: 4+ years of experience in software engineering, with strong hands-on experience in backend development and building scalable production systems. Strong proficiency in Python and solid software engineering fundamentals, including clean architecture, testing, and maintainable code practices. Experience working with data-intensive applications, databases, and SQL, including data modeling and query optimization. Exposure to modern data engineering, cloud, or infrastructure environments, with familiarity in tools such as Terraform, Kubernetes, Docker, or similar technologies. Understanding of CI/CD pipelines, Infrastructure as Code, and general engineering best practices. Interest in AI/ML ecosystems and willingness to work closely with Data Science and AI teams on productionizing ML solutions. Familiarity with cloud platforms and modern data stack technologies such as AWS, Snowflake, Spark, or DBT is considered a strong plus. Ownership mindset and comfort working in evolving, fast-moving environments where systems and processes are still being built. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.

🏢 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: High-impact Staff Engineer (P5) role focused on re-architecting and scaling a core SaaS platform from 100M to 10B+ rows. The position centers on designing distributed systems, leading a shift to microservices, and setting architectural standards for a multi-product ecosystem. This is a highly autonomous role driving platform evolution, scalability, performance, and security. 🗂️ Requirements: Expert-level Python and Django knowledge, Proven experience building platforms or infrastructure, Experience with massive datasets (1B+ rows), Strong background in distributed systems design, Experience designing and implementing microservices architectures, Demonstrated performance optimization expertise, Ability to independently design and deliver complex technical solutions 📃 Skills: Python, Django, Microservices, DistributedSystems, Architecture, Scalability, PerformanceOptimization, AWS, InfrastructureAsCode 🏢 Description: Position: Staff Engineer (P5) Working model: Remore Employment form: B2B We are partnering with a fast-growing, venture-backed SaaS company that is revolutionizing the Sales Performance Management space. As we scale from mid-market to enterprise, we are looking for a Staff Engineer (P5) to join the Platform Pillar. This is a high-impact role for a true “Platform Builder” who thrives on architecture and solving complex scalability challenges. The Role & Opportunity You will be a key architect of the core platform. We are not looking for a product-focused developer, but a systems thinker who will build the foundation upon which all our products sit. The current platform handles 100M rows, and they are gearing up for a 10x scale to 10B rows. Re-architecturing has just begun and you will be a primary driver of this transformation. This role requires high autonomy—you will be expected to identify problems, design technical solutions, and execute without “hand-holding.” Key Responsibilities Platform Evolution: Build and scale the core platform infrastructure to support high-volume data (10B+ rows). Architecture & Principles: Set the technical standards and architectural direction for the platform pillar. Focus on high-level design and robust principles. Microservices Shift: Lead the transition from a single-product architecture into a robust microservices and multi-product ecosystem. Autonomy: Take full ownership of complex technical problems, from discovery to implementation. Mentorship & Impact: Influence engineering standards across the entire organization, ensuring high performance and security. Requirements Deep Backend Expertise: Expert-level Python and Django knowledge. (FE matters very little in this role). Platform Builder Mindset: Proven track record of building platforms, internal tools, or infrastructure. Scale Experience: Experience working with massive data sets (dealing with 1B+ rows) and performance optimization. Architecture Heavy: Ability to design distributed systems and microservices at scale. Ownership: A history of being autonomous and delivering solutions to complex problems without supervision. Nice to have Experience from a single-product company that successfully shifted into microservices and a multi-product environment. Experience with AWS architecture and infrastructure-as-code. The Offer Base Compensation: Up to 150,000 USD annually (B2B) Equities: Significant stock option package. Unlimited PTO: We value results over hours. Hardware: Latest Apple hardware (MacBook Pro). Well-being: Quarterly mental health days and work anniversary stipends. Remote-first: Fully remote culture with a multicultural team.

🏢 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