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Big Data Engineer - ML Analytics & Search(m/w/x)
Developing PB-scale sensor data indexing and search pipelines at an automotive manufacturer. 3-5 years experience with PB-scale query optimization and distributed compute frameworks expected. Six weeks annual leave, Christmas bonus.
Anforderungen
- University degree in Computer Science, Engineering, or related field
- 3-5 years experience in big data or data engineering with analytics and search focus
- Strong Python and SQL skills
- Experience with distributed compute frameworks
- Experience with columnar/analytical storage and PB-scale query optimisation
- Familiarity with search/indexing technologies (full-text, vector/embedding, metadata catalogues)
- Production experience with Kubernetes and AWS/Azure/Google Cloud
- Hands-on experience with infrastructure-as-code
- Experience with automotive measurement data (MDF4/ASAM MDF or MCAP)
- Experience with embedding-based retrieval, dataset management, stream processing, or graph-based metadata systems
Aufgaben
- Develop high-performance search pipelines for PB-scale data.
- Develop high-performance query pipelines for PB-scale data.
- Build and operate sensor data indexing systems.
- Build and operate sensor data cataloguing systems.
- Extract metadata from sensor data.
- Implement signal-level indexing.
- Perform scene tagging.
- Develop embedding-based similarity search.
- Implement distributed compute pipelines for data evaluation.
- Perform batch statistics analysis.
- Conduct data distribution analysis.
- Generate annotation coverage reports.
- Perform data quality scoring.
- Build fast analytical queries for interactive exploration.
- Develop dataset assembly pipelines.
- Automate assembly of datasets.
- Version training and evaluation datasets.
- Register training and evaluation datasets.
- Optimize data cost and performance.
- Implement intelligent data partitioning.
- Utilize tiered storage solutions.
- Apply caching strategies.
- Perform query pushdown.
- Operate observability stacks for data pipelines.
- Monitor query latency dashboards.
- Track pipeline health.
- Manage data freshness monitors.
Berufserfahrung
- 3 - 5 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- SQL
- Kubernetes
- AWS
- Azure
- Google Cloud
- MDF4
- ASAM MDF
- MCAP
Benefits
Flexibles Arbeiten
- Flexible working hours
Mehr Urlaubstage
- Six weeks annual leave
Attraktive Vergütung
- Overtime compensation
Boni & Prämien
- Christmas bonus
- Profit sharing
Weiterbildungsangebote
- Development opportunities
Sicherer Arbeitsplatz
- Job security
Mitarbeiterrabatte
- Discounted BMW & MINI conditions
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Big Data Engineer - ML Analytics & Search(m/w/x)
Developing PB-scale sensor data indexing and search pipelines at an automotive manufacturer. 3-5 years experience with PB-scale query optimization and distributed compute frameworks expected. Six weeks annual leave, Christmas bonus.
Anforderungen
- University degree in Computer Science, Engineering, or related field
- 3-5 years experience in big data or data engineering with analytics and search focus
- Strong Python and SQL skills
- Experience with distributed compute frameworks
- Experience with columnar/analytical storage and PB-scale query optimisation
- Familiarity with search/indexing technologies (full-text, vector/embedding, metadata catalogues)
- Production experience with Kubernetes and AWS/Azure/Google Cloud
- Hands-on experience with infrastructure-as-code
- Experience with automotive measurement data (MDF4/ASAM MDF or MCAP)
- Experience with embedding-based retrieval, dataset management, stream processing, or graph-based metadata systems
Aufgaben
- Develop high-performance search pipelines for PB-scale data.
- Develop high-performance query pipelines for PB-scale data.
- Build and operate sensor data indexing systems.
- Build and operate sensor data cataloguing systems.
- Extract metadata from sensor data.
- Implement signal-level indexing.
- Perform scene tagging.
- Develop embedding-based similarity search.
- Implement distributed compute pipelines for data evaluation.
- Perform batch statistics analysis.
- Conduct data distribution analysis.
- Generate annotation coverage reports.
- Perform data quality scoring.
- Build fast analytical queries for interactive exploration.
- Develop dataset assembly pipelines.
- Automate assembly of datasets.
- Version training and evaluation datasets.
- Register training and evaluation datasets.
- Optimize data cost and performance.
- Implement intelligent data partitioning.
- Utilize tiered storage solutions.
- Apply caching strategies.
- Perform query pushdown.
- Operate observability stacks for data pipelines.
- Monitor query latency dashboards.
- Track pipeline health.
- Manage data freshness monitors.
Berufserfahrung
- 3 - 5 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- SQL
- Kubernetes
- AWS
- Azure
- Google Cloud
- MDF4
- ASAM MDF
- MCAP
Benefits
Flexibles Arbeiten
- Flexible working hours
Mehr Urlaubstage
- Six weeks annual leave
Attraktive Vergütung
- Overtime compensation
Boni & Prämien
- Christmas bonus
- Profit sharing
Weiterbildungsangebote
- Development opportunities
Sicherer Arbeitsplatz
- Job security
Mitarbeiterrabatte
- Discounted BMW & MINI conditions
Über das Unternehmen
BMW Group
Branche
Automotive
Beschreibung
Das Unternehmen bietet spannende Praktika im Bereich Markenerlebnis und Eventmanagement und legt großen Wert auf Gleichbehandlung und Chancengleichheit.
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