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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Engineer - Data Operations (all genders) - **Company:** STARK GmbH - **Location:** München, Germany - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon S3, BigQuery, Cloud Storage, Databases, Continuous Integration, Data Infrastructure, Extract Transform Load (ETL), Data Security, Identity and Access Management, Python (Programming Language), PostgreSQL, Metadata, Operational Data Store, DataOps, Software Engineering, SQL Databases, Management of Software Versions, Data Logging, Backend, Google Cloud Functions, Data Management, Lidar, Data Pipelines, Docker, Data Generation - **Published:** July 27, 2026 - **Apply:** https://www.adzuna.de/details/5816487675 ## About the Role * Strong Python * Solid SQL/PostgreSQL, including schema design * Experience with data modeling and metadata systems * Experience designing and operating ETL/data pipelines * Docker and CI/CD basics * Hands-on with object storage (GCS, S3, or similar) * Good software engineering hygiene: tests, docs, typing, logging * Organized and pragmatic: you can prioritize between a quick fix and a proper solution, and you know when each is right * Not allergic to support tasks - but technical enough to automate the support away * Comfortable coordinating with external vendors and non-technical stakeholders, * Familiarity with ML datasets and labeling workflows (images, video, lidar; annotation formats like COCO) * Experience with synthetic data generation or GenAI-assisted data workflows (auto-labeling, data augmentation, foundation-model-based curation) * Experience with GCP services beyond storage (BigQuery, Cloud Run, IAM) * Experience with data versioning / dataset tooling (DVC, LakeFS, FiftyOne, or similar) * Experience in a startup environment - comfortable with ambiguity and changing priorities * Exposure to robotics data formats (ROS bags, MCAP, PX4 logs) ## Description Data is the fuel of STARK's AI stack - you build the engine that makes it usable. You own the software backbone of our data platform: the metadata systems, ETL pipelines, data contracts, catalogs, databases, and internal tools that let engineers find, understand, validate, and reuse terabytes of multi-sensor field data in minutes, not days. You treat data context as a product: structured, searchable, version-aware, documented, and traceable from raw recording to processed asset, annotation delivery, dataset, and downstream ML workflow. Today, much of this is manual, scattered, or implicit - your job is to automate it away, support labeling efforts with the right data tooling, and turn operational data into reliable systems., * Design, implement, and maintain our metadata database and data catalog (datasets, recordings, sensors, labels, lineage) * Build and operate ETL/ingest pipelines that bring field recordings, synthetic data, and external deliveries into our cloud storage (GCP) * Own the data management and labeling lifecycle end-to-end: coordinate and communicate with external labeling companies and data subcontractors, track deliveries, run QA reports, and build the operational workflows they work in * Develop internal enabling tools for the whole AI organization: dataset search and filtering, APIs/backend, dashboards, and self-service data access * Run data migrations and indexing jobs; keep the catalog consistent and fast as data volume grows * Handle admin support and user access management - and then automate these support tasks so they stop being manual work * Establish good engineering hygiene in a young codebase: tests, typing, docs, logging, CI/CD * Shape the long-term architecture and vision of the data platform together with the team ## Related Videos - [How to develop an autonomous car end-to-end: Robotic Drive and the mobility revolution](https://www.wearedevelopers.com/videos/22-how-to-develop-an-autonomous-car-end-to-end-robotic-drive-and-the-mobility-revolution) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies](https://www.wearedevelopers.com/videos/251-remote-driving-on-plant-grounds-with-state-of-the-art-cloud-technologies) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Fullstack developer salary in Germany [2023]](https://www.wearedevelopers.com/magazine/197-fullstack-developer-salary-in-germany-2023) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [Backend Developer Salary in Germany [2023]](https://www.wearedevelopers.com/magazine/196-backend-developer-salary-in-germany-2023) - [Software Developer Salary in Germany [2023]](https://www.wearedevelopers.com/magazine/194-software-developer-salary-in-germany-2023) - [Frontend Developer Salary in Germany [2023]](https://www.wearedevelopers.com/magazine/195-frontend-developer-salary-in-germany-2023) - [Data Analyst Salary Germany](https://www.wearedevelopers.com/magazine/277-data-analyst-salary-germany)