Senior Data Engineer

🏢 Summary: Senior Big Data Engineer role focused on designing and optimizing large-scale data processing solutions using Spark and Scala within the financial sector. The position involves building resilient data pipelines, supporting production systems, and collaborating in Agile teams to deliver scalable data platforms. Hybrid work model based in Warsaw with up to two remote days per week. 🗂️ Requirements: 3-5 years experience in big data engineering, Strong expertise in Spark, Proficiency in Scala or Java, Knowledge of Python, Experience with DevOps practices, Experience with CI/CD tools, Understanding of microservices architecture, Fluent English, Legal right to work in the European Union 📃 Skills: Spark, Scala, Java, Python, DevOps, CI/CD, Microservices, Airflow, Git, Scrum, BigData 🏢 Description: Empower data-driven innovation — shape the future of financial technology! Warsaw-based opportunity with hybrid work model (up to 2 remote days per week). As a Senior Big Data Engineer (Spark/Scala) , you will be working for our client, a leader in structured finance within the global banking industry. You will contribute to building and optimizing a cutting-edge data platform that supports complex business processes and facilitates collaboration across multiple stakeholders in the finance sector. Join us to drive impactful data solutions that fuel digital transformation and open new avenues for growth. Your main responsibilities: Design and develop solutions for collecting, transforming, and processing large datasets efficiently. Analyze data from multiple sources and translate insights into technical specifications. Implement and industrialize reliable, scalable, and resilient data processing jobs using Spark and Scala. Conduct code reviews and collaborate with team members to ensure continuous improvement. Contribute to agile teams delivering value through Scrum cycles, supporting innovative project delivery. Stay up-to-date with evolving big data technologies and implement best practices. Support applications, troubleshoot production issues, and ensure high quality standards. Produce comprehensive technical documentation, test plans, and project artifacts. You're ideal for this role if you have: 3-5 years of professional experience in big data engineering, ideally within banking or finance. Strong expertise in Spark and Java or Scala, with additional knowledge of Python, DevOps, CI/CD tools, and microservices. Fluency in English (Polish and French are a plus). Analytical mindset with excellent problem-solving skills. Proactive attitude and strong teamwork skills across global teams. Effective communication skills and ability to work across different time zones. It is a strong plus if you have: Knowledge of Airflow, GIT, and modern data architecture strategies. Experience with Agile methodologies and delivering solutions in fast-paced environments. Language Required for the role: Fluent English (required) Eligibility for the role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.

🏢 Summary: Full-time Data Engineer role focused on building and maintaining scalable, cloud-based data platforms for large-scale analytics. The position involves developing end-to-end data pipelines and collaborating with researchers and data professionals to enable data exploration and insight generation. 🗂️ Requirements: 3+ years experience in Data Engineering or similar role, Strong Python skills, Experience with Spark or Scala, Experience with big data technologies, Ability to design scalable data solutions 📃 Skills: Python, Spark, Scala, Cloud, ETL, BigData, GraphDB 🏢 Description: Role Title: Data Engineer Location: Warsaw, hybrid Contract Type: Umowa o Pracę - full time employment 25000-36000 zl gross/month - negotiable (depending on years of experience) A growing research-focused team is looking for a Data Engineer to build and support data platforms that help professionals extract insights from large, complex datasets. This role involves working closely with researchers, analysts, and data scientists to design scalable data solutions. What you’ll do Build and maintain end-to-end data pipelines (ingestion, transformation, delivery) Develop cloud-based data infrastructure for large-scale analytics Work with teams to enable data exploration and visualization Evaluate and prototype new big data technologies Requirements 3+ years experience in Data Engineering or similar role Strong Python development skills Experience with Spark or Scala Interest or experience in big data technologies Ability to design innovative solutions to data challenges Nice to have • Experience with graph databases

🏢 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: Senior Java Developer role focused on building and maintaining backend microservices in the Credit Data Sourcing domain within a banking environment. The position involves designing data flows, system integrations, and scalable business logic, as well as supporting production incidents. Work is performed in an Agile team with hybrid presence in Poland. 🗂️ Requirements: Strong experience with Java and backend development, Experience designing and maintaining microservices, Experience with data flows and data sourcing systems, Experience in integration-heavy environments, Ability to analyze end-to-end data flow across systems, Ability to assess impact on upstream and downstream systems, Experience working with distributed systems, Experience in incident analysis and troubleshooting, Understanding of financial or credit domain systems 📃 Skills: Java, Microservices, Dataflows, Integrations, Distributed, Banking, Credit, Agile, Scrum, Troubleshooting 🏢 Description: OFFER DETAILS: Industry: Banking Location: Warsaw / Gdańsk / Łódź Work model: Hybrid – 3 days per week in the office required Rate: up to 160 PLN/hour net + VAT Contract type: B2B Overview: The Senior Java Developer role focuses on the development and maintenance of backend services in the Credit Data Sourcing domain. This position requires strong involvement in data flows, integrations, and business logic, along with close collaboration with Business Analysts, Product Owners, and other stakeholders. The role also includes participating in production support and incident resolution. Main Responsibilities: Design, develop, and maintain Java-based microservices. Implement and optimize data flows and integrations between systems. Collaborate with analysts on user stories, acceptance criteria, and solution design. Translate business requirements into scalable technical solutions. Support incident analysis and troubleshooting including logs and root cause analysis. Contribute to refinement sessions and technical design discussions. Ensure high-quality code, testing, and performance. Key Requirements: Experience in data flows and data sourcing systems. Experience in integration-heavy environments. Ability to understand end-to-end data flow across systems. Ability to analyze impact of changes on upstream/downstream systems. Experience in the financial/credit domain is advantageous. Strong analytical and problem-solving skills. Good communication with both technical and business stakeholders. Ownership mindset and responsibility for delivery. Comfortable working in complex, distributed systems. Nice to Have: Experience with frontend frameworks like Angular or React. Experience in credit risk and banking systems. Experience with event-driven architectures. Performance tuning in data-heavy systems. Other Details: This position is based in Poland, specifically in Gdańsk, Warsaw, or Łódź. The role operates within an Agile/Scrum team environment, emphasizing close collaboration and regular alignment around releases. Ideal candidates will thrive in a dynamic, interdisciplinary setting.

🏢 Summary: Long-term Senior Software Engineer role building a cloud-based financial data platform from scratch. The position focuses on designing and developing scalable, real-time data processing solutions in Azure with strong influence on architecture and engineering standards. You will create backend services and data pipelines in a modern, evolving data environment. 🗂️ Requirements: Strong programming skills in Python or Java or C#, Experience with cloud platforms (Azure preferred), Experience building backend services or data processing components, Experience working with data pipelines and ensuring data consistency, Understanding of software design and clean code principles, Experience with CI/CD pipelines, Experience with version control systems 📃 Skills: Python, Java, C#, Azure, Cloud, CI/CD, Backend, Datapipelines 🏢 Description: As a Senior Software Engineer, you’ll be working on data-driven solutions within the financial data and analytics space. This is a long-term collaboration on a project being built from scratch, giving you real influence over architecture, technology choices, and engineering standards from day one. You’ll be shaping platforms that process large-scale, real-time data used across global financial systems, in a modern and evolving data environment. Key responsibilities Design and develop scalable solutions in cloud environment (Azure) Build and maintain data processing components and services Work with data pipelines and ensure data consistency across systems Develop cloud-based applications and services Collaborate with Engineering, Architecture and Product teams Contribute to clean code, CI/CD, automation and system reliability Take part in code reviews and technical discussions Ideal candidate profile Strong programming skills in Python or Java or C# Experience working with cloud platforms (Azure preferred) Experience in building backend services or data processing components Understanding of software design, clean code and good engineering practices Experience with CI/CD pipelines and version control systems Ability to work independently and as part of a team Good communication skills Nice to have Experience with Spark / PySpark / Databricks Experience with data platforms or data engineering concepts Familiarity with event-driven architectures (Kafka, Event Hubs or similar) Experience with Azure data ecosystem (e.g. Fabric) Experience with containers / Kubernetes (AKS) Conditions Form of cooperation: UoP + KUP 50% Salary range: 18 000 - 30 000 PLN gross/month + yearly bonus depends on the results Hybrid work model: 3 days per week in the Gdynia office Benefits: private medical care, Multisport card, employee pension scheme Recruitment steps Call with a KUBO recruiter (approx. 30 min.) Interview with the client (max. 2 rounds) Decision and feedback

🏢 Summary: Hybrid Java Developer role in the banking sector focused on building and integrating data flows for Financial Crime Prevention systems. The position involves developing microservices-based solutions using Spring Boot, maintaining existing code, and collaborating on DevOps-driven delivery processes. Candidates will work with modern data, messaging, and containerization technologies in a cross-functional environment. 🗂️ Requirements: Proficiency in DevOps methodology, Strong knowledge of Java, Experience with Spring Boot and microservices, Experience with PostgreSQL, Experience with DataStage (ETL), Strong SQL knowledge, Familiarity with Kubernetes, Familiarity with Bitbucket, Familiarity with Jenkins, Understanding of Kafka 📃 Skills: Java, Spring, SpringBoot, Microservices, PostgreSQL, SQL, DataStage, Kubernetes, Bitbucket, Jenkins, Kafka, Maven, Liquibase, JOLT 🏢 Description: Industries: Banking Location: Hybrid - 3 per week from Gdańsk or Gdynia Rate: 165 pln/h Introduction & Summary We are seeking experienced Java Developers to contribute to the integration and process data flows within the Financial Crime Prevention area. The ideal candidates should possess robust expertise in Java, particularly with the Spring Boot framework, alongside a solid understanding of DevOps practices and relevant database technologies. Main Responsibilities The Java Developers will be tasked with: Implementing functionalities related to financial crime prevention. Collaborating with cross-functional teams to enhance data integration. Maintaining and improving existing codebases. Documenting processes and contributing to technical specifications. Participating in code reviews and ensuring code quality. Key Requirements Proficiency in the DevOps methodology. Strong knowledge of Java, especially with Spring Boot framework and microservices. Experience with Postgres DB, DataStage (ETL), and SQL. Familiarity with Kubernetes, Bitbucket, and Jenkins. Understanding of Kafka and its applications. Able to work effectively in a team environment. Excellent interpersonal and communication skills. Technologies: Java 21, Kubernetes, Kafka, Maven, PostgreSQL, Spring Boot, Liquibase, and JOLT. Nice to Have Experience with Apache Camel. Familiarity with Oracle SOA Suite. Knowledge of SCRUM methodologies. Understanding of CDC concepts, particularly Debezium.

🏢 Summary: Hybrid Java Developer role in the banking sector focused on building and integrating data flows within the Financial Crime Prevention area. The position involves developing microservices-based solutions, enhancing existing systems, and supporting data integration using modern DevOps practices. The role requires strong backend expertise and experience with distributed systems and databases. 🗂️ Requirements: Proficiency in DevOps methodology, Strong knowledge of Java, Experience with Spring Boot, Experience with microservices architecture, Experience with PostgreSQL, Experience with SQL, Experience with DataStage (ETL), Familiarity with Kubernetes, Familiarity with Bitbucket, Familiarity with Jenkins, Understanding of Kafka 📃 Skills: Java, Spring, SpringBoot, Microservices, PostgreSQL, SQL, DataStage, Kubernetes, Bitbucket, Jenkins, Kafka, Maven, Liquibase, JOLT 🏢 Description: Industries: Banking Location: Hybrid - 3 per week from Gdańsk or Gdynia Rate: 165 pln/h Introduction & Summary We are seeking experienced Java Developers to contribute to the integration and process data flows within the Financial Crime Prevention area. The ideal candidates should possess robust expertise in Java, particularly with the Spring Boot framework, alongside a solid understanding of DevOps practices and relevant database technologies. Main Responsibilities The Java Developers will be tasked with: Implementing functionalities related to financial crime prevention. Collaborating with cross-functional teams to enhance data integration. Maintaining and improving existing codebases. Documenting processes and contributing to technical specifications. Participating in code reviews and ensuring code quality. Key Requirements Proficiency in the DevOps methodology. Strong knowledge of Java, especially with Spring Boot framework and microservices. Experience with Postgres DB, DataStage (ETL), and SQL. Familiarity with Kubernetes, Bitbucket, and Jenkins. Understanding of Kafka and its applications. Able to work effectively in a team environment. Excellent interpersonal and communication skills. Technologies: Java 21, Kubernetes, Kafka, Maven, PostgreSQL, Spring Boot, Liquibase, and JOLT. Nice to Have Experience with Apache Camel. Familiarity with Oracle SOA Suite. Knowledge of SCRUM methodologies. Understanding of CDC concepts, particularly Debezium.

🏢 Summary: Scala/Spark Developer role focused on building and optimizing scalable data processing applications and distributed systems using modern big data technologies. The position involves developing ETL/ELT pipelines, improving Spark performance, and collaborating on international AI and data engineering projects. The offer includes flexible working conditions, private healthcare, training opportunities, and a B2B salary range of 28,500–30,000 PLN + VAT. 🗂️ Requirements: Commercial experience with Scala in production environments, Knowledge of functional programming concepts in Scala, Experience with Scala type system, collections, sbt, and testing frameworks, Hands-on experience with Apache Spark, Experience with Spark SQL and DataFrame/Dataset API, Experience designing and maintaining ETL/ELT pipelines, Knowledge of Spark performance optimization techniques, Experience troubleshooting Spark applications using Spark UI, Experience with large-scale distributed data processing, Understanding of software engineering best practices and code quality 📃 Skills: Scala, Spark, SparkSQL, DataFrame, Dataset, ETL, ELT, sbt, ScalaTest, munit, SparkUI, Kafka, Airflow, AWS, EMR, S3, Glue, Azure, GCP, Dataproc, Databricks, Hadoop, Hive, DeltaLake, Parquet, Avro, SQL, Docker, Kubernetes, Git, CI/CD, Cats, ZIO, Akka, Pekko, Python, Java 🏢 Description: Scala/Spark Developer We are looking for a Scala/Spark Developer to join an AI-first software engineering company delivering innovative AI, data, cloud, and IoT solutions for clients across Europe and beyond. As part of the engineering team, you will design, develop, and optimize scalable data processing solutions, build high-performance distributed systems, and work with modern big data technologies on challenging international projects. Responsibilities Design, develop, and maintain scalable data processing applications using Scala and Apache Spark; Build, optimize, and maintain ETL/ELT pipelines processing large volumes of data; Develop efficient Spark applications using Spark SQL and the DataFrame/Dataset API; Optimize Spark jobs by improving partitioning strategies, shuffle operations, caching, and join performance; Troubleshoot and resolve performance issues using Spark UI and monitoring tools; Collaborate with data engineers, software developers, and stakeholders to design scalable data processing solutions; Participate in code reviews and contribute to software quality, performance, and engineering best practices. Requirements Strong commercial experience developing production applications in Scala, including functional programming concepts (immutability, pattern matching, higher-order functions), Scala type system, collections, sbt, and testing frameworks such as ScalaTest or munit, with the ability to write clean, maintainable, production-quality code; Proven hands-on experience with Apache Spark, including Spark SQL, DataFrame/Dataset API, designing and maintaining ETL/ELT pipelines, performance optimization (partitioning, shuffle optimization, broadcast joins, caching), and troubleshooting using Spark UI; Experience working in production environments with large-scale data processing and distributed data pipelines; Strong understanding of software engineering best practices, code quality, performance optimization, and maintainability. Nice to have Experience with Kafka and Spark Structured Streaming; Experience with Airflow or similar workflow orchestration tools; Experience with cloud platforms such as AWS (EMR, S3, Glue), Azure, GCP (Dataproc), or Databricks; Knowledge of the big data ecosystem, including Hadoop, Hive, Delta Lake, Parquet, and Avro; Experience with SQL, data modeling, data warehouses, and data lake architectures; Experience with Docker, Kubernetes, Git, and CI/CD pipelines; Familiarity with Scala libraries such as Cats, ZIO, Akka, or Pekko; Knowledge of Python or Java. We offer B2B salary: 28 500 -30 000 PLN + VAT; Flexible working conditions; Private healthcare, Multisport card, and professional training opportunities.