Data Engineer ADAS Fleet Analytics

Mercedes Benz; San Jose (CA); On-site; USD 118,000 - 148,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with employer match

Up to 15 company-paid holidays

Paid time off

Tuition assistance

Wellness/Fitness reimbursement

Job summary

Mercedes-Benz Research & Development North America, Inc. seeks a Data Engineer for the US ADAS Data & Forensics team to build pipelines that convert raw vehicle signals into KPIs, dashboards, and campaign-health metrics.

You will own end-to-end data lifecycle, from real-time ingestion to Delta Lake processing, with PySpark, and deploy APIs and dashboards while collaborating with engineers calibrating ADAS functions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
• 3+ years of professional experience.
• 2-5 years in data engineering or big-data analytics with production pipeline ownership.
• Strong Python, PySpark DataFrame API and SQL skills.
• Experience with Delta Lake, Iceberg, Hudi, or Parquet.
• Experience with automated testing for data pipelines and Git workflows.

Responsibilities

• Design and maintain scalable telemetry pipelines using Event Hub, Delta Lake MERGE, schema evolution, and blue/green data deployments.
• Own campaign and fleet management, including enrollment rosters and ingestion-monitoring.
• Develop fleet KPIs for engineering, operations, and management.
• Build ML-ready data infrastructure for video and signal pipelines and feature stores.
• Operate the Azure data platform (ADLS Gen2, Synapse Spark) and support CI/CD.
• Write automated tests and contribute to documentation and code reviews.

Skills

Python

PySpark

SQL

Data engineering

Testing pipelines

Git workflows

Education

Bachelor's or Master's in CS/Data Eng

Tools

Delta Lake

Iceberg

Hudi

Parquet

Job description

Job Description - Data Engineer, ADAS Fleet Analytics (MER00048Z4)

Description

Position Overview

Mercedes-Benz uses large-scale vehicle telemetry to evaluate, monitor, and improve its Advanced Driver Assistance Systems. As a Data Engineer on the US ADAS Data & Forensics team, you will build and operate the data pipelines that turn raw vehicle signals into trusted KPIs, fleet dashboards, and campaign-health monitoring for management and the engineers who calibrate ADAS functions. You will own the full data lifecycle, including real-time ingestion, binary protocol decoding, Bronze/Silver/Gold processing with PySpark and Delta Lake, and delivery through APIs and dashboards. You will also manage data campaigns end to end, including VIN enrollment, fleet-health tracking, coverage-gap detection, and the Sold to Consented to Capable to Active vehicle funnel. The architecture is evolving toward applied AI, and you will build the data infrastructure required for vision-language models, LLM-based event classification, embedding retrieval, and model-based event scoring.

Relocation assistance (domestic or international) is not provided for this position.

Job 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, 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, and support Terraform-managed infrastructure and CI/CD.
• Write automated tests, maintain documentation alongside code, and participate in code reviews and incident response.

Qualifications

Minimum Qualifications

• 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, and 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 technical and non-technical stakeholders.

Strongly Preferred

• Medallion or other layered data-processing patterns.
• Cloud data-platform experience in Azure, AWS, or GCP.
• Production data-quality practices, including deduplication, idempotency, and data contracts.
• Time-series, IoT, or vehicle-telemetry data.

Nice to Have

• DuckDB or PyArrow; FastAPI or analytical API delivery; blue/green data deployments.
• ML data infrastructure, including feature stores, embedding pipelines, vector databases, or video pipelines.
• Fleet or campaign management for vehicle or IoT programs.
• Automotive data privacy, including CCPA; ADAS or connected-vehicle domain knowledge.
• Azure Data Engineer or Databricks certification.
• English required; German is an advantage.

The successful candidate’s starting pay will be determined based on a wide range of factors, including, but not limited to, job-related education, skills, and experience, geographic location, and market conditions. The current salary range for this position is as follows and may be modified in the future: $118,200 - $147,700.

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 the International Traffic in Arms Regulations (ITAR), 22 C.F.R. Parts 120-130. As such, Mercedes-Benz Research & Development North America may be required to obtain an export license or authorization in accordance with United States law.

Why should you apply?

Here at MBRDNA, you create digital ecosystems around cars, you design a language between humans and machines, you make a car even more intelligent - you make the new reality for cars. MBRDNA was honored as one of the "Best Places to Work" by BuiltIn in January 2024, a testament to our commitment to creating an exceptional work environment. At each of our offices, we foster a culture of collaboration and continuous learning, ensuring every team member can thrive and innovate.

Benefits for Full-Time

• 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
• Internships & Contractors excluded from Full-Time Employee benefits

MBRDNA is an equal opportunity employer (EOE) and strongly supports diversity in the workforce.

Mercedes-Benz Research & Development North America, Inc.

Organization

Mercedes-Benz Research & Development North America, Inc.

Primary Location

United States of America-California-San Jose

Work Locations

2708 Orchard Parkway 2708 Orchard Parkway San Jose 95134