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: Senior Data Engineer role in the banking sector focused on building scalable Big Data solutions supporting Financial Crime Prevention processes. The position involves developing distributed data pipelines and streaming applications using Spark and Scala in a Continuous Delivery environment. It is a long-term hybrid project with an immediate start. 🗂️ Requirements: Senior-level experience in Big Data and ETL, Senior-level Scala proficiency, Senior-level Spark and Spark SQL expertise, Strong SQL knowledge, Experience with Data Testing, Practical experience with distributed large-scale data systems 📃 Skills: Scala, Spark, SparkSQL, SQL, ETL, BigData, DataTesting 🏢 Description: 📍 Location: Gdańsk / Gdynia / Warsaw (hybrid) 🚀 Start: ASAP 💶 Rate: 35–45 EUR/h About the role We are looking for a Senior Data Engineer to work on a long-term project for a leading client in the banking industry . In this role, you will implement complex data requirements and build scalable solutions that support the client’s Financial Crime Prevention processes . Responsibilities Build distributed Big Data processing pipelines handling large volumes of structured and unstructured data in near real-time Develop streaming applications connecting multiple internal and external data sources Transform and enrich data with Apache Spark for analytics, visualization, and search Deliver clean, high-quality datasets for downstream systems Work closely with DevOps, QA, and Product teams in a Continuous Delivery environment Requirements Experience with Big Data / ETL / SQL / Data Testing (Senior level) Senior-level Scala Senior-level Spark and Spark SQL Practical experience with distributed, large-scale data systems Recruitment process First interview: Conversation with our Talent Team Technical interview: Discussion with one of our developers Final interview: Meeting with the CTO

🏢 Summary: Senior Data Engineer role focused on designing and building scalable serverless data ingestion pipelines in AWS within the healthcare domain. The position emphasizes strong Python engineering, cloud architecture leadership, and implementation of modern data platforms and DevOps practices. The role involves driving technical excellence and delivering reliable, high-impact data solutions in an international environment. 🗂️ Requirements: 10+ years of experience in Python programming, Strong software engineering skills in data processing, Extensive experience with AWS Cloud and Serverless Architecture, Hands-on experience with AWS Lambda, S3, and Cognito, Experience building E2E automated tests for data pipelines, Practical knowledge of Data Mesh and Medallion Architecture, Experience with Infrastructure as Code using AWS CDK or Terraform, Experience with CI/CD pipelines using GitLab or GitHub Actions, Experience with ETL/ELT processes and dbt, Experience working with GraphQL, Minimum B2 level English proficiency 📃 Skills: Python, AWS, Lambda, S3, Cognito, Boto3, DataMesh, Medallion, CDK, Terraform, GitLab, GitHubActions, ETL, ELT, dbt, GraphQL, CI/CD 🏢 Description: We are looking for a highly skilled Data Engineer to join our client in the healthcare sector. Our requirements: Technical Expertise: Python Programming: 10+ years of experience with strong Software Engineering skills focused on data processing. AWS & Serverless: Extensive experience with AWS Cloud, specifically focusing on Serverless Architecture and services (including AWS Lambda , AWS S3 Tables , and AWS Cognito ). Automated Testing: Proven experience in developing End-to-End (E2E) automated tests to ensure pipeline reliability, utilizing tools such as Boto3 for AWS resource validation. Data Concepts: Practical knowledge of Data Mesh and Medallion Architecture , along with general data processing and analysis. DevOps & IaC: Hands-on experience with Infrastructure as Code ( AWS CDK or Terraform ) and CI/CD pipelines ( GitLab pipelines or GitHub Actions ). Modern Tooling: Experience with ETL/ELT solutions, dbt , and GraphQL . Communication & Soft Skills: English Language: Minimum B2 level , enabling smooth daily technical and business communication in a global environment. Collaboration: Excellent communication skills and the ability to thrive in a collaborative, international team. Standards: A strong commitment to high standards of ethics, quality (Clean Code), and reliable delivery. Nice to have: Experience with Snowflake and SQL . Knowledge of Data Vault 2.0 modeling. Experience with Databricks . Familiarity with the Microsoft ecosystem: C# / .Net, T-SQL, SQL Server , and Azure DevOps . Experience with Star Schema database modeling. Knowledge of Descriptive Statistics. Your responsibilites: Design and build scalable Data Ingestion pipelines within the AWS cloud ecosystem. Lead technical delivery and implementation of core platform components, ensuring architectural integrity across the entire data lifecycle. Collaborate with Engineering Managers and cross-functional teams across the globe and Poland. Drive technical excellence by improving team processes, architecture standards, and engineering best practices. Support and consult with stakeholders to ensure successful delivery of high-impact, data-driven solutions. Contribute to the growth and maturity of the team’s cloud and data engineering capabilities. We offer: Challenging role within the company that creates innovative solutions. Work in international environment on demanding projects. Remote work model. Subsidized private medical care, life insurance, multisport card. Integration meetings. Employee referral program. If you have a deep expertise in Python and AWS , and building scalable Serverless data architectures is where you truly excel, this is the perfect role for you!

🏢 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: 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: The offer is for an experienced Python Data Engineer to build scalable, cloud-based data and analytics solutions for global financial institutions. The role focuses on designing distributed data pipelines, enhancing system reliability, and developing financial and AI-driven data platforms. You will work with modern cloud and AI tools to advance enterprise data architecture and analytics capabilities. 🗂️ Requirements: 4+ years of professional experience in Python data or software engineering, Strong knowledge of data architecture, data modeling, and data warehousing, Advanced SQL skills and complex query writing, Experience building scalable distributed data pipelines, Hands-on experience with cloud environments (AWS preferred), Understanding of event-driven architectures, Experience with debugging and system reliability practices 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 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: Opportunity for an experienced Python Data Engineer to build scalable data platforms and analytics systems for global financial institutions. The role focuses on designing cloud-based data pipelines, enhancing system reliability, and integrating modern AI tools into engineering workflows. You will collaborate across distributed teams to deliver high-quality solutions in enterprise data, risk analytics, and AI-driven metadata applications. 🗂️ Requirements: 4+ years of professional experience in software or data engineering using Python, Strong knowledge of data architecture, data modeling, and data warehousing, Ability to write complex SQL queries and perform advanced debugging, Experience building scalable, distributed data pipelines in cloud environments, Experience with AWS, Familiarity with event-driven architectures 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For: Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance