Senior Data Engineer (Data Platform)

Join Unzer, a fast-paced and innovative company in the financial services industry. As a Senior Data Engineer, you will be responsible for the end-to-end health and evolution of our data platform. You will design, build, run, monitor, and troubleshoot data pipelines, manage cloud infrastructure, and investigate and resolve production incidents. You will have the freedom to choose the right tools and approaches for each use case, and your work will have a direct impact on the company's decision-making process. Enjoy a flexible work environment, a learning budget for personal development, and the opportunity to work from home up to 80% of the time.

• Own data pipelines end to end: design, build, run, monitor, and troubleshoot across orchestration, transformation, lake ingestion, and cloud infrastructure.
• Build and maintain Apache Airflow workflows to schedule transformation jobs, ingestion tasks, and containerized workloads.
• Develop dbt models in Redshift (or a similar warehouse), including incremental strategies, data quality tests, and CI validation.
• You have solid AWS experience across object storage, containers, managed ETL, serverless, data warehousing, replication (for example, DMS), IAM, and related analytics services such as Athena and Glue
• You have experience with Git, CI/CD, and Docker, and can maintain deployment pipelines and manage container image lifecycle
• You have 5+ years of data engineering or related experience, with production-grade pipeline development primarily in Python
• You can work independently while also collaborating well with analytics and platform stakeholders
• You have excellent knowledge of SQL and a strong understanding of data warehouse concepts, with hands-on experience in Redshift (or similar) for modeling, ingestion, performance optimization, and data integrity
• You have a proven ability to own projects from requirements gathering through production monitoring and incident response
• You have hands-on experience with ELT/ETL flows using dbt and workflow orchestration with Apache Airflow, including DAG design, operators, and troubleshooting
• You have a strong operational mindset and can troubleshoot systematically across a distributed, multi-repository platform
• Financial services or payments data pipelines experience
• Search or indexing experience, Avro, or schema registries
• Additional languages used in ingestion or operational repos, such as Go
• Event-driven architecture (Kafka or similar)
• Infrastructure as Code (Terraform, CloudFormation)