Data Engineer, ADAS Fleet Analytics

Build telemetry data pipelines that translate vehicle signals into trusted KPIs, fleet dashboards, and ADAS campaign-health monitoring for engineering and management teams. On the US ADAS Data & Forensics team at Mercedes-Benz Research & Development North America, you will help shape ML-ready infrastructure for ADAS event scoring, operating at large scale on the Azure data platform with production ownership across ingestion, processing, and delivery.

Work onsite in San Jose, CA with a role focused on real-time ingestion, Bronze/Silver/Gold processing with Delta Lake, and reliable operations through CI/CD and incident response practices.

Why you will like working here

• Medical, dental, and vision insurance for employees and their families
• 401(k) with employer match
• Up to 15 company-paid holidays
• Paid time off (flexible time off for salaried employees), sick time, and parental leave
• Tuition assistance program
• Wellness/Fitness reimbursement programs

Responsibilities

• Design and maintain scalable telemetry pipelines using Event Hub, Medallion architecture, Delta Lake MERGE, schema evolution, and blue/green data deployments.
• Own campaign and fleet management including enrollment rosters, ingestion-completeness monitoring, VIN reconciliation, and automated coverage alerts.
• Develop fleet KPIs for engineering, operations, and management, including safety event and takeover analysis, data freshness and pipeline health, and trends and cohort comparisons.
• Build ML-ready data infrastructure for SSR recordings, including video and signal pipelines, embedding stores, feature-engineering layers, and model-output integration into Gold.
• Operate the Azure data platform with ADLS Gen2, Synapse Spark, Event Hub, and Container Apps; support infrastructure managed with Terraform and CI/CD.
• Write automated tests, maintain documentation alongside code, participate in code reviews, and support incident response.

Requirements

• 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.
• Strong Python, PySpark DataFrame API, and performance-tuning skills, plus SQL 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 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.

Tech stack

• Event Hub, Delta Lake (including Delta Lake MERGE)
• PySpark, Python, SQL
• ADLS Gen2, Synapse Spark, Container Apps
• Terraform, CI/CD
• Iceberg, Hudi, Parquet, Git
• FastAPI, DuckDB, PyArrow, vector databases

Additional details

• Employment type: Vollzeit (Full-time)
• Start date: sofort
• Compensation: USD 118,200 - 147,700 per year (range may be modified in the future)
• Position number: MER00048Z4
• Relocation assistance: not provided for this position
• Export control: may involve access to export-controlled technology/software; Mercedes-Benz Research & Development North America may be required to obtain an export license or authorization under US law
• Benefits note: Internships & Contractors excluded from Full-Time Employee benefits