Data Engineering Manager General Motors Austin Texas
Overview
Lead a team of data engineers building Customer data platforms for OnStar Connected Services Customer Marketing Personalization AI Advanced Analytics. This technical leadership role builds scalable cloud-native data products across multi-cloud Lakehouse architecture focusing on Databricks Distributed Data Processing near Real-Time Streaming AI ML Generative AI. Seeking technology leader combining deep technical expertise with people leadership.
What You'll Do11
- 1Lead mentor and grow high-performing data engineering team including performance management career development hiring onboarding
- 2Define and execute technical roadmap for Customer Marketing and OnStar Digital data products using cloud-agnostic portable architecture enabling interoperability across Azure GCP AWS and other platforms while supporting multi-cloud strategy
- 3Architect design and build scalable batch streaming API and event-driven data pipelines using Databricks Apache Spark Delta Lake and Unity Catalog
- 4Own end-to-end delivery of data engineering initiatives from product requirements to operational support post deployment
- 5Drive modernization from legacy platforms to cloud-native multi-cloud Lakehouse architectures
- 6Enable AI and Machine Learning by building trusted reusable governed data products supporting predictive analytics GenAI and LLM applications
- 7Collaborate with architecture and platform teams to align reference architectures standards and reusable components
- 8Champion engineering excellence through CI/CD Infrastructure as Code Data Observability automated testing metadata management and data quality
- 9Optimize platform performance scalability reliability and cloud cost efficiency
- 10Work with Business Product Marketing Analytics Security and Architecture teams to deliver business outcomes and technical innovation
- 11Foster culture of innovation continuous learning experimentation and engineering excellence
Requirements17
- 1Bachelor’s degree in computer science engineering information systems or related field
- 27+ years experience in Data Engineering Software Engineering or production grade Distributed Data Platforms
- 33+ years proven experience leading and managing data engineering or software engineering teams
- 4Deep expertise with Databricks Apache Spark Delta Lake Unity Catalog Python SQL and modern Lakehouse architectures
- 5Experience designing cloud-native solutions across Azure AWS or GCP
- 6Strong understanding of data modeling data governance observability security and engineering best practices
- 7Exposure to AI-first engineering concepts including Generative AI Agentic AI Retrieval Augmented Generation vector search and LLM-powered applications
- 8Strong experience building large-scale distributed batch and streaming data pipelines
- 9Leadership communication and stakeholder management translating business needs into technical solutions
- 10Experience with Databricks AI capabilities such as MLflow Mosaic AI Delta Live Tables Feature Store Vector Search Genie Spaces
- 11Experience building Customer 360 Marketing Personalization CDP or Connected Services platforms
- 12Implementation of DataOps MLOps practices including CI/CD pipelines and automated testing for data pipelines
- 13Experience with streaming technologies such as Kafka or Azure Event Hubs
- 14Integration with data sources like Shopify Heap Adobe SDK and AppsFlyer
- 15Knowledge of Data Mesh Data Products and modern cloud-native architecture patterns
- 16Understanding of data privacy security and regulatory considerations for enterprise data
- 17Operating critical data platforms with strong SLAs and support processes
Salary Insight
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