Mercedes-Benz Research & Development North America is seeking a Data Engineer to help the US ADAS Data & Forensics team turn large-scale vehicle telemetry into trusted KPIs, fleet dashboards, and campaign-health monitoring. If you enjoy building and operating production data systems that support applied AI and ML-ready event scoring, this role offers hands-on ownership across the full data lifecycle.
This position is onsite in San Jose, CA, with a compensation range of $118,200 - $147,700 per year. Full-time benefits include medical, dental, and vision coverage, 401(k) with employer match, up to 15 company-paid holidays, flexible time off for salaried employees, sick time, parental leave, tuition assistance, and wellness or fitness reimbursement programs. Please note that internships and contractors are excluded from Full-Time Employee benefits.
What you will do
- Design and operate scalable telemetry data pipelines using Event Hub, Medallion architecture, Delta Lake MERGE, schema evolution, and blue/green data deployments.
- Own campaign and fleet management activities such as enrollment rosters, ingestion-completeness monitoring, VIN reconciliation, and automated coverage alerts.
- Develop fleet KPIs for engineering (including safety events and takeover analysis), operations (including data freshness and pipeline health), and management (including trends and cohort comparisons).
- Build ML-ready data infrastructure, including video and signal pipelines for SSR recordings, embedding stores, feature-engineering layers, and model-output integration into Gold.
- Operate the Azure data platform, including ADLS Gen2, Synapse Spark, Event Hub, and Container Apps, while supporting Terraform-managed infrastructure and CI/CD.
- Maintain quality through automated tests, code documentation alongside the codebase, and active participation in code reviews and incident response.
What you bring
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field (equivalent experience may be considered).
- 3+ years of professional experience.
- 2-5 years of experience in data engineering or big-data analytics with production pipeline ownership.
- Python and PySpark DataFrame API with performance-tuning skills, plus SQL skills including window functions and aggregations.
- Experience with a columnar or transactional data lake technology such as Delta Lake, Iceberg, Hudi, or managed Parquet.
- Experience with automated testing for data pipelines and Git-based development workflows.
- Ability to diagnose production failures, including schema conflicts, data skew, and memory issues, and communicate trade-offs to both technical and non-technical stakeholders.
- Strongly preferred: cloud data-platform experience in Azure, AWS, or GCP.
- Nice to have: ML data infrastructure, including feature stores, embedding pipelines, vector databases, or video pipelines.
Technologies you may work with
- Event Hub, Delta Lake, PySpark, Delta Lake MERGE, ADLS Gen2, Synapse Spark, Container Apps
- Terraform, CI/CD
- Python, SQL, Iceberg, Hudi, Parquet, Git
- FastAPI, DuckDB, PyArrow, vector databases
Position details
Work type: Vollzeit (Full-time). Start date: sofort. Travel/relocation: Relocation assistance (domestic or international) is not provided for this position.
Export control
This position may involve access to export-controlled technology, hardware, or software under the Export Administration Regulations (EAR), 15 C.F.R. Parts 730-774, and possibly technical data, defense articles and defense services subject to ITAR, 22 C.F.R. Parts 120-130. Mercedes-Benz Research & Development North America may be required to obtain an export license or authorization in accordance with US law.
Requisition (STELLENNUMMER): MER00048Z4
