Synapse Spark Engineer Jobs

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Data Engineer, ADAS Fleet Analytics

Mercedes-Benz Research & Development North America, Inc. San Jose, CA

San Jose, CA

Today

$118k - $148k/yr Full time Adls Gen2 Application Security Artificial Intelligence

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Job Description

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

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