Senior/Lead Data Engineer

Job description

Join our team in Warsaw, where we’re collaborating on a cutting-edge fintech venture with a global industry leader. Together with our Partner – Klarna, we’re building an IT hub designed to drive innovation in digital payment solutions. We’re on the lookout for top-tier engineers who thrive in dynamic, forward-thinking environments. Spyrosoft is leading the recruitment process, facilitating a seamless experience for candidates who are ready to shape the future of online shopping and payments.

This opportunity is ideal for engineers who value independence, proactiveness, and flexibility. Our engagement begins with a B2B contract through Spyrosoft, transitioning to a direct contract with our Partner.

We offer a hybrid work model in Warsaw’s vibrant Wola district. English fluency and eligibility to work in Poland are essential, as is the successful completion of a background check to meet the rigorous standards of the financial domain.

Our process:

• CV selection
• Initial recruitment screening
• Technical interview
• Online logic test
• Cultural fit interview

Requirements

• • Minimum 5 years of experience as a Data Engineer with proficiency in SQL, PySpark, and Python. Essential for developing scalable data pipelines and performing data transformations.
  • Strong experience with frameworks such as Apache Airflow, AWS Glue, Kafka, and Redshift, critical for batch and real-time data handling.
  • Hands-on experience with AWS services, including Lambda, S3, CloudWatch, SNS/SQS, and Kinesis, for managing cloud-based data processing and serverless architecture.
  • Proficiency in Git for version control, Airflow for scheduling, Terraform for infrastructure-as-code, and Ansible for automation.
  • Experience monitoring and maintaining ETL pipelines to ensure high performance and reliability.
  • Understanding of CI/CD processes to automate testing, deployment, and versioning.
  • Ability to design and manage horizontally scalable systems that can efficiently handle large data volumes.

Nice to Have:

• API Development: Experience in building APIs for data exchange using REST, GraphQL, OpenAPI, or FastAPI.
• Data Platform Innovation: Familiarity with Data Mesh concepts and Self-Service tools, with experience building scalable data platforms, pipelines, and transformations.