Backend Engineer - Java

🏢 Summary: Senior backend engineering role focused on designing and operating large-scale batch and streaming data pipeline platforms with strong reliability and performance requirements. The position involves building distributed systems, pipeline orchestration services, and cloud-native platform capabilities using Java and modern data technologies. The role also includes technical leadership, CI/CD improvements, and collaboration across international engineering teams. 🗂️ Requirements: Strong backend engineering experience with Java, Experience building production-grade distributed systems, Expertise in software architecture and system design, Experience with high-throughput and low-latency systems, Knowledge of REST APIs and microservices, Hands-on experience with AWS and cloud-native design, Experience with Docker and Kubernetes, Experience with Flink, Spark, or Kafka, Familiarity with CI/CD pipelines and DevOps practices, Experience with Jenkins, GitLab, Git, and JIRA, Strong communication skills 📃 Skills: Java, Flink, Spark, Kafka, AWS, EMR, S3, REST, Microservices, Docker, Kubernetes, Jenkins, GitLab, Git, JIRA, HTTP 🏢 Description: The Pipeline Management team builds and operates a core platform that powers large-scale batch and streaming data pipelines across HERE’s Data Platform. Our platform enables internal teams and customers to design, deploy, and operate data pipelines at scale, supporting mission-critical workloads with strong reliability and performance requirements. Lead the design and development of pipeline management services and APIs Own and evolve key platform components, including pipeline orchestration, scheduling, and workflow state management Drive architecture for high-throughput, low-latency distributed systems Partner with Product and engineering teams to deliver scalable data platform capabilities Mentor engineers and provide technical leadership across a distributed team Improve system reliability, observability, and SLA adherence for production services Contribute to CI/CD, automation, and engineering best practices across the platform Technology Stack: You will work with a modern data platform ecosystem including: Data Processing: Apache Flink, Apache Spark Backend & Services: Java (primary), REST APIs, microservices Streaming & Messaging: Apache Kafka Cloud & Infrastructure: AWS (EMR, S3) Platform Services: Pipeline Service, Scheduler, State Service, Coordinator CI/CD & Tooling: Jenkins, GitLab pipelines, Git, JIRA Who are you? Strong backend engineering experience with Java (preferred), building production-grade distributed systems Expertise in software architecture and system design Experience building and operating high-throughput, low-latency, highly reliable distributed systems Solid understanding of REST APIs, HTTP, and microservices architectures Hands-on experience with cloud platforms (AWS preferred) and cloud-native design Experience with containerization and orchestration (Docker, Kubernetes) Experience with data processing and streaming systems (e.g., Flink, Spark, Kafka) Strong familiarity with CI/CD pipelines and engineering tools (e.g., Jenkins, GitLab, Git, JIRA) Experience applying DevOps practices to improve system reliability and delivery velocity Strong communication skills with the ability to clearly explain complex concepts Nice to Have Experience with pipeline orchestration platforms or workflow engines Exposure to large-scale data platforms or multi-tenant systems Experience with cloud platform migrations or modernization initiatives What we offer: Work on on globally deployed automotive navigation and mapping products Collaboration with an experienced, international engineering organization Truly international team of fantastic & talented people from 60+ countries worldwide, working from strong tech hubs located in Europe, the US, and Asia, along with multiple smaller locations Flexible working hours & a flexible approach to office vs. remote work Medical coverage for you and your family Yearly variable bonus This role is eligible for the Creative Tax Incentive scheme in Poland (KUP) Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case)

🏢 Summary: The offer is for a Data Engineer/DevOps professional to build and maintain scalable data platforms and cloud infrastructure, automate data workflows using CI/CD and Infrastructure as Code, and optimize data pipelines for high availability and security. The role focuses on managing data processing environments and supporting model deployment in collaboration with data teams. 🗂️ Requirements: Proficiency in Linux/Unix administration, Strong Shell scripting skills, Advanced knowledge of Python, Advanced knowledge of SQL, 3–5 years experience in Data Engineering or DevOps, Degree in Computer Science, Data Engineering, or related field 📃 Skills: Linux, Unix, Shell, Python, SQL, Azure, Spark, Databricks, Docker, Kubernetes, Terraform, Ansible, Hadoop, Kafka, CICD 🏢 Description: Key Responsibilities Infrastructure Management: Build and maintain scalable data platforms and cloud-based infrastructure. Automation: Implement CI/CD pipelines for data workflows and automate manual processes using Infrastructure as Code (IaC). Pipeline Optimization: Monitor, troubleshoot, and optimize data processing jobs to ensure high availability. Security & Compliance: Ensure data integrity and security across all environments. Collaboration: Work closely with Data Scientists and Engineers to streamline the deployment of data models. Requirements Systems & Scripting: Strong proficiency in Linux/Unix administration and Shell scripting. Programming: Advanced knowledge of Python and SQL . Mindset: Exceptional analytical and problem-solving skills. Education: Degree in Computer Science, Data Engineering, or a related technical field. Experience: 3–5 years of proven experience in Data Engineering or a DevOps-related role. Nice-to-have Cloud & Big Data: Hands-on experience with Azure , Apache Spark , and Databricks . DevOps Tools: Proficiency with Docker , Kubernetes , CI/CD tools, and IaC (e.g., Terraform, Ansible). Data Ecosystems: Familiarity with Big Data technologies such as Hadoop or Kafka .

🏢 Summary: DevOps Engineer role focused on supporting and scaling modern data platforms by combining DevOps practices with data engineering expertise. The position involves building and maintaining CI/CD pipelines, managing cloud-based data infrastructure, and ensuring reliable, automated data workflows. You will collaborate with data teams to optimize performance, scalability, and security of data solutions. 🗂️ Requirements: 4–5 years experience in DevOps or similar role, Hands-on experience with Databricks, Strong experience with AWS, Experience building and maintaining CI/CD pipelines with Jenkins, Background in data engineering or data platforms, Basic to intermediate Python knowledge, Understanding of ETL/ELT processes, Knowledge of distributed data systems 📃 Skills: Jenkins, Databricks, AWS, Python, CICD, ETL, ELT, DevOps, DataEngineering, Cloud, DistributedSystems 🏢 Description: About the Role We are looking for a DevOps Engineer with a strong data background to support and scale modern data platforms. In this role, you will work at the intersection of DevOps and Data Engineering , ensuring reliable, automated, and efficient data pipelines and environments. You will be responsible for maintaining and improving CI/CD processes, supporting cloud-based data platforms, and collaborating with data engineers and analytics teams to enable smooth data operations. Key Responsibilities Design, implement, and maintain CI/CD pipelines using Jenkins . Manage and optimize data platforms based on Databricks . Build and maintain cloud infrastructure on Amazon Web Services . Support deployment, monitoring, and troubleshooting of data pipelines and workflows. Collaborate closely with data engineers to improve reliability and performance of data solutions. Automate infrastructure and operational processes. Ensure best practices in security, scalability, and performance across the platform. Required Skills & Experience 4–5 years of experience in a DevOps Engineer or similar role. Hands-on experience with Databricks . Strong experience with Amazon Web Services . Experience building and maintaining CI/CD pipelines using Jenkins . Background in data engineering or experience working with data platforms. Basic to intermediate knowledge of Python . Understanding of data pipelines, ETL/ELT processes, and distributed data systems. Strong problem-solving skills and ability to troubleshoot complex issues. Good communication skills and ability to work in cross-functional teams.

🏢 Summary: Senior Java Software Engineer role focused on building complex, data-driven solutions for financial services within a data engineering initiative. The position involves designing and optimizing data sourcing, processing, and ingestion pipelines using modern cloud and big data technologies. You will work on mission-critical systems supporting portfolio management, investment operations, and regulatory platforms. 🗂️ Requirements: Bachelor’s degree in Computer Science or relevant certification, Proficiency in Java, Proficiency in Spark, Proficiency in Python, Experience with data streaming and real-time and batch processing, Experience with CI/CD pipelines (ADO, GitHub or GitLab), Experience with TDD, Experience with cloud architecture (Azure, AWS or GCP), Experience with Hibernate and relational databases, Knowledge of software design principles 📃 Skills: Java, Spark, Python, AWS, Azure, GCP, Databricks, Kubernetes, Hibernate, SQL, GitHub, GitLab, ADO, CI/CD, TDD 🏢 Description: We are looking for a Senior Java Software Engineer to join our team working on complex, data-driven solutions for the financial services domain. The role is part of a data engineering initiative focused on data sourcing, processing, and ingestion for mission-critical applications. You will contribute to projects supporting Portfolio Management, Investment Operations, Regulatory Reporting, ETF platforms, Data and Workflow Management, as well as systems used for Investment Strategy and Research. This is an excellent opportunity to work with modern cloud technologies and large-scale data platforms in a highly impactful environment. This role offers a hybrid model, with 3 days per week working from the client's office in Krakow. If you're ready to make an impact in a dynamic environment, we want to hear from you! Responsibilities Design, develop, and maintain high-performance Java-based applications for data engineering solutions Build and optimize data sourcing, transformation, and ingestion pipelines Develop and integrate services using AWS cloud services Implement robust persistence layers using Hibernate and relational databases Collaborate with data engineers, analysts, and business stakeholders to deliver scalable solutions Ensure high code quality through best practices, code reviews, and automated testing Troubleshoot, debug, and optimize performance of existing systems Contribute to architectural decisions and technical design discussions Requirements Bachelor’s degree in Computer Science or relevant certification Working with modern technologies such as data streaming, real-time and batch processing; experience with Databricks and Kubernetes is advantageous Proficiency with Java, Spark and Python Significant experience with DevOps CI/CD pipelines and concepts - ADO, GitHub or Gitlab Significant experience using TDD Well versed in Cloud architecture and have delivered to one or more; Azure (preferred), AWS or GCP Experience of software design principles Worked with modern tech – data streaming, real-time & batch processing Databricks and Kubernetes 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.

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, platform reliability, and cloud-native data infrastructure to improve performance, scalability, and observability of global data ecosystems. Hybrid work model with competitive salary and comprehensive benefits. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend engineering skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience in cloud environments (AWS preferred), Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven or streaming architectures, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable and reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, cloud-native infrastructure, and data platform reliability to improve performance and scalability of global data systems. It is a hands-on role working with large-scale data pipelines, streaming, and cloud environments. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend programming skills in Python, Java, or Kotlin, Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience with cloud environments, preferably AWS, Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven architectures or streaming systems, Understanding of end-to-end data flow and data modeling, Experience designing scalable and reliable data systems, Experience with infrastructure automation tools 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, cloud-native infrastructure, and data platform reliability to support global, data-intensive applications. The engineer will enhance performance, scalability, and observability of production datastores across a multi-region environment. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend programming skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience with cloud environments, preferably AWS, Hands-on experience with relational or NoSQL databases, Experience with large-scale data pipelines and data processing systems, Experience with event-driven architectures or streaming/batch processing, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable, high-performance, reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .

🏢 Summary: Remote Senior DevOps Engineer role focused on modernizing and scaling a cloud-native Data & AI Platform. The position involves refactoring AWS and Airflow infrastructure, implementing Infrastructure as Code for Snowflake, and building next-generation workflow orchestration. The role also supports CI/CD automation and infrastructure for Data Science, ML, and AI systems. 🗂️ Requirements: Strong experience with AWS, Strong experience with Terraform, Hands-on experience with Apache Airflow, Experience with CI/CD tools (GitLab, GitHub Actions, Jenkins), Experience with Snowflake and Infrastructure as Code, Knowledge of modern workflow orchestration tools (Prefect, Dagster, Temporal), Experience supporting Data Science, ML, or AI platforms 📃 Skills: AWS, Terraform, Airflow, Snowflake, GitLab, GitHubActions, Jenkins, Prefect, Dagster, Temporal, CI/CD, IaC, Python 🏢 Description: Senior DevOps Engineer (Data Platform & AI) 📍 Remote from Poland We are looking for a Senior DevOps Engineer to support the evolution of our Data & AI Platform. Key responsibilities: • Refactoring AWS-based Data Platform infrastructure • Refactoring and optimization of Apache Airflow infrastructure • CI/CD runner setup and automation • Infrastructure setup for Data Science and ML pipelines • Infrastructure as Code (Terraform) for Snowflake environments • Design and implementation of a next-generation workflow engine to replace Airflow • Infrastructure setup for AI systems, including MCP servers Requirements: • Strong AWS and Terraform experience • Hands-on experience with Airflow infrastructure • CI/CD expertise (GitLab, GitHub Actions, Jenkins) • Experience with Snowflake and Infrastructure as Code • Understanding of modern workflow orchestration tools (Prefect, Dagster, Temporal, etc.) • Experience supporting Data Science, ML, or AI platforms Nice to have: • GCP / BigQuery exposure • Experience with LLM or AI infrastructure This is an opportunity to build and modernize a cloud-native data platform while helping shape the future AI infrastructure of the organization.

🏢 Summary: Design and scale high-throughput data pipelines on cloud platforms to support advanced analytics and AI-driven products. The role focuses on building distributed data architectures in AWS and Databricks, ensuring performance, governance, and data quality. You will collaborate with AI/ML teams to deliver scalable, production-grade data solutions. 🗂️ Requirements: 3+ years of data engineering experience, Strong Python programming skills, Experience with Spark or Scala, Experience building distributed data pipelines in cloud environments, Knowledge of data modeling and data warehousing principles, Bachelor’s or Master’s degree in Computer Science or Engineering 📃 Skills: Python, Spark, Scala, AWS, Glue, EMR, Fargate, StepFunctions, Databricks, SQL, APIs, GenAI, GraphDB 🏢 Description: Data Engineer – Cloud & AI Platforms We’re looking for a Data Engineer to design and scale high-throughput data pipelines supporting advanced analytics and AI-driven products. What You’ll Do Architect and maintain distributed data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions) Ingest and process large volumes of structured and unstructured data (internal, market, third-party, alternative sources) Collaborate with AI/ML and engineering teams to design scalable data architectures and APIs Optimize performance and cost using Spark and cloud-native best practices Implement data governance, privacy, lineage, and access controls Build automated validation, monitoring, and data quality frameworks Evaluate emerging GenAI and data tooling to enhance platform capabilities What You Bring 3+ years of experience in data engineering Strong Python and experience with Spark or Scala Proven experience building distributed pipelines in cloud environments Solid understanding of data modeling, architecture, and warehousing principles Innovative problem-solving mindset Bachelor’s or Master’s degree in Computer Science or Engineering Nice to have: Experience with graph databases.

🏢 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.