Senior Data Engineer Jobs in Rochester, MI (NOW HIRING)

Job Description

• Build and operate the telemetry data platform that powers connected vehicle analytics, AI, quality engineering, and software-defined vehicle innovation at global scale
• Build and operate large-scale telemetry pipelines that ingest, process, and publish vehicle data at enterprise scale
• Develop batch and streaming solutions using Databricks, Spark, Event Hubs, and cloud-native technologies
• Create reliable, production-grade data products that support analytics, AI, engineering, and operational decision-making
• Implement data quality, validation, monitoring, and observability capabilities that proactively identify issues before they impact consumers
• Design systems that are scalable, resilient, cost-efficient, and easy to operate
• Build tooling and frameworks that make it easier for teams to develop and deploy trusted data assets
• Troubleshoot performance bottlenecks and optimize large-scale distributed workloads
• Improve platform reliability through automation, CI/CD, Infrastructure as Code, and engineering best practices
• Partner with product, analytics, AI, and engineering teams to deliver trusted telemetry data at scale
• Help raise the engineering bar through mentorship, technical leadership, and operational excellence

• How do we reliably process billions of telemetry events every day?
• How do we detect data quality issues before business users find them?
• How do we make telemetry data easier to trust, discover, and reuse?
• How do we scale streaming and batch workloads without runaway cloud costs?
• How do we provide observability into thousands of pipelines and data products?
• How do we make telemetry data available to analytics, AI, and engineering teams faster and more reliably?

• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related technical field
• 5+ years of experience building large-scale data platforms, distributed systems, or data engineering solutions
• Strong hands-on experience with Spark and distributed data processing
• Strong programming skills in Python or Scala
• Expert-level SQL skills
• Experience with Databricks or similar large-scale analytical platforms
• Experience building cloud-native solutions in Azure, AWS, or GCP
• Experience with streaming technologies such as Event Hubs, Kafka, Pulsar, or similar platforms
• Experience building and operating highly reliable production data pipelines
• Experience implementing observability, monitoring, alerting, and operational support capabilities
• Experience designing and enforcing data quality controls, validation frameworks, and reliability standards
• Experience optimizing distributed workloads for performance, scalability, and cost efficiency
• Experience with CI/CD, Infrastructure as Code, and automation practices
• Strong troubleshooting, communication, and problem-solving skills

• Reliability
• Observability
• Data quality
• Performance
• Scalability
• Cost efficiency
• Operational excellence

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