Staff Data Engineer: AI-Ready Pipelines & Platform Lead

General Motors; Michigan; Hybrid; USD 160,000 - 212,000; Full time

Benefits offered by this job

Company vehicle program

Relocation benefits

Job summary

General Motors seeks a principal-level Data Engineer (Level 8) to lead complex initiatives, set direction for data domains, and improve data delivery patterns across the organization. This hybrid role anchors in data engineering with an AI data enablement focus, collaborating with data scientists and business partners to deliver governed data products and scalable AI-ready data.

The role requires broad autonomy, a strong technical authority stance, and the ability to influence roadmaps across

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field, or equivalent experience.
• 8+ years of relevant full-time experience in data engineering or closely related roles; or equivalent depth of knowledge.
• Strong, hands-on experience in data engineering, including: End-to-end pipeline development (ingestion, transformation, orchestration, monitoring).
• Data modeling (batch and streaming), data integration, and production support for enterprise data platforms.
• Building and operating highly reliable, scalable data products in production environments.
• Extensive experience designing and optimizing batch and streaming data pipelines using Databricks, Apache Spark, Delta Lake, and modern cloud data patterns.
• Proven experience supporting AI or machine-learning use cases through high-quality data preparation, feature-ready datasets, experimentation workflows, and model-development enablement.
• Proficiency in: Python or Scala.
• SQL, including performance tuning and working with large-scale datasets.
• Relational and non-relational data storage technologies (e.g., data warehouses, NoSQL, key-value stores, document stores).
• Deep experience with cloud platforms – Azure strongly preferred; AWS or GCP also considered.
• Extensive experience designing, building, and optimizing scalable batch and streaming data pipelines using Databricks (Apache Spark, Delta Lake) to support Medallion Architecture and other modern data patterns.
• Demonstrated experience with modern cloud data platforms, distributed processing, and production-grade data pipelines, including: Data quality frameworks and observability.
• Orchestration tools and job scheduling.
• Performance optimization and cost management.
• Proven ability to work independently and lead through influence, managing broad, ambiguous technical challenges and delivering high-impact solutions with minimal guidance.
• Experience driving cross-functional collaboration across engineering, analytics, product, and business teams to deliver data solutions that enable measurable business outcomes, including AI and advanced analytics.
• Solid understanding of statistics, machine learning, experimentation, and data mining concepts used to drive informed decisions.
• Demonstrated ability to: Prepare and explore data at scale.
• Support model development workflows.
• Help validate analytical outputs and production model behavior in partnership with data scientists.
• Ability to translate complex analytical and AI needs into scalable, maintainable data solutions and help move data science work from exploration into repeatable, governed, and automated delivery patterns.
• Strong communication and storytelling skills to connect technical work with business value and to convert complex findings and trade-offs into clear, actionable recommendations for diverse audiences.

Responsibilities

• Design, build, and productionize reliable, scalable data pipelines and data products in Azure Databricks that support AI, analytics, and operational use cases across multiple business domains.
• Lead end-to-end transformation of raw data from numerous, heterogeneous source systems into trusted, well-structured, and governed datasets.
• Define and champion architecture, design patterns, and best practices that can be adopted across teams.
• Drive strategic improvements in internal processes, delivery patterns, and technical solutions that support broader data strategy.
• Solve complex data engineering problems using advanced analytical techniques with strong ownership.
• Partner with data scientists, analysts, software engineers, and business leaders to ensure data is accessible and aligned to outcomes.
• Lead AI and data science enablement by delivering high-quality, feature-ready data and scalable experiments for models.
• Provide technical leadership for large, multi-sprint initiatives across teams.

Skills

Databricks

Spark

Delta Lake

Python/Scala

SQL

Data modeling

Cloud platforms Azure

MLOps

Data pipelines

Cross-functional collaboration

Education

Bachelor’s degree in CS/SE/Data Eng or related

Advanced degree (Master’s/PhD)

Tools

Azure

AWS

GCP

Job description

General Motors seeks a principal-level Data Engineer (Level 8) to lead complex initiatives, set direction for data domains, and improve data delivery patterns across the organization. This hybrid role anchors in data engineering with an AI data enablement focus, collaborating with data scientists and business partners to deliver governed data products and scalable AI-ready data.

The role requires broad autonomy, a strong technical authority stance, and the ability to influence roadmaps across