Design and maintain data pipelines, build ETL pipelines, and integrate data streams. Ensure data quality, observability, and reproducibility. Collaborate with embedded, edge, ML, and software teams.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Relocation to Germany or Netherlands:
Senior AI Solution Engineer with 5+ years of experience
We notice multiple open positions in Germany and Netherlands, with below skillset. We enable aspiring candidates to unlock their full potential and find opportunity to work in Germany. Apply if your skills are matching and you are interested in investing in yourself and relocate to Germany.
Responsibilities
- Design and maintain data pipelines from edge cloud data platform
- Build ETL pipelines using AWS Glue and cloud-native data services
- Integrate data streams from event-based edge systems
- Process and structure motion tracking data from camera-based arena systems
- Develop and maintain datasets for ML model training and evaluation
- Build reliable data products and curated datasets for researchers and engineers
- Support ad-hoc analysis, experimentation, and exploration by data scientists
- Ensure data quality, observability, lineage, and reproducibility across pipelines
- Collaborate with embedded, edge, ML, and software teams to ensure high-quality data capture
- Improve the data infrastructure used to analyze and optimize swarm behavior and system performance
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Your Profile
You enjoy turning complex system data into clean, reliable datasets that power real-world AI systems
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Must-haves
- 3+ years experience as a Data Platform Engineer or in a similar role
- Strong experience with Python and SQL
- Experience building cloud-based data pipelines
- Familiarity with AWS data services (S3, Glue, Athena, etc.)
- Experience working with streaming or event-driven data systems
- Understanding of data modeling and data product design
- Experience supporting ML workflows and data scientists
- Strong attention to data quality, validation, and reproducibility
- Comfortable working with complex multi-system datasets (hardware, sensors, logs, telemetry)
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Nice-to-have
- Experience processing IoT, robotics, or telemetry dat
- Experience with time-series or sensor data pipeline
- Familiarity with SageMaker or ML data platform
- Experience with computer vision datasets or motion tracking system
- Experience designing data lakes or lakehouse architecture
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