Software Engineer Data Platform
Summary
Build and maintain the data platform that feeds AI pipelines, including data quality workflows, secure APIs, event-driven pipelines, and internal tooling in Python and AWS.
You will maintain and evolve the data platform powering AI pipelines. You will design data quality and transformation workflows, build secure APIs and internal tooling, improve CI/CD and integration testing, and manage data assets, governance, lineage, access control, schemas, observability, and reliable event-driven pipelines in the Munich office.
Responsibilities
- Design and operate automated data quality pipelines
- Develop transformation processes for analytics and model training datasets
- Instrument systems with metrics, alerts, and recovery mechanisms
- Build internal tooling and dashboards
- Build secure APIs and backend services for large datasets
- Improve CI/CD pipelines, integration tests, and dependency management
- Own data asset lineage, access control, and schema enforcement
- Handle structured and semi-structured data
- Build resilient pipelines with versioning and schema evolution
Requirements
- 5+ years of proficiency in Python
- Strong system design fundamentals
- Experience designing and building secure, performant APIs
- Experience with Docker and Kubernetes
- Experience with AWS services and Terraform
- Experience designing and operating data ingestion and transformation workflows
- Exposure to Snowflake or other SQL-based analytics platforms
- Familiarity with CI/CD pipelines and version control
- Fundamentals in data modeling and schema design
- Experience with MongoDB
- Knowledge of data partitioning and large-scale dataset optimization
- Experience with event-driven pipelines using SQS, SNS, Lambda, or Step Functions