Data Platform Engineer – Data Operations (all genders)

8 hours ago

Berlin, Germany or Munich, GermanySenior

Responsibilities

Design, write, and maintain typed, tested Python software and ETL pipelines for ingesting and processing flight data, rosbags, video, and external data deliveries.
Build tools for video subsampling, frame extraction, dataset packaging, self-service data access, and internal data operations.
Design and maintain metadata databases and data catalogs covering datasets, recordings, sensors, labels, and lineage.
Own technical workflows for data curation and labeling, including vendor coordination, delivery tracking, and automated quality assurance.
Develop backend APIs, dashboards, and data-access tools for searching, filtering, and understanding multi-sensor data.
Establish software engineering practices including testing, typing, documentation, logging, and CI/CD pipelines.
Migrate legacy data, manage access, and automate recurring support and operational tasks.

Strong experience writing clean, maintainable Python software with typing and testing.
Proven experience designing, building, and operating ETL or data-ingestion pipelines.
Strong SQL, schema design, data modeling, and metadata-system knowledge; PostgreSQL is preferred.
Hands-on experience with object storage such as GCP/GCS or S3, plus basic containerization with Docker.
Strong familiarity with Unix-based systems, shell scripting, standard Unix tools, and Linux environments.
Ability to work pragmatically in a changing startup environment and balance short-term fixes with durable architecture.
Experience coordinating cross-functionally with external vendors and non-technical stakeholders on data labeling and curation.
Preferred experience with synthetic data generation, GenAI-assisted workflows, data versioning, computer-vision annotation formats, advanced GCP services, robotics data formats, or large-scale multimodal data.

5,001-10,000 employees