Senior Data Engineer

Why GMF Technology? Innovation isn't just a talking point at GM Financial, it's how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We're committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry. Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact. Flexible hybrid work environment (onsite 2 days a week/3 days remote) at our Arlington (AOC1), TX office.

Please note:

We are unable to provide any type of sponsorship for this position at this time.

About The Role:

The Senior Data Engineer is responsible for architecting and implementing resilient data ingestion pipelines and designing normalized database schemas optimized for transactional processing. This role ensures seamless integration between vendor systems and internal applications, maintaining high availability and performance for operational data services. The Senior Data Engineer collaborates with cross-functional teams to deliver secure, efficient, and scalable solutions that support GM Financial's operational data strategy. This team member will design and maintain an Operational Data Store (ODS) that serves as the authoritative source for integrated applications, while implementing strategies for synchronization, conflict resolution, and resilience. The role requires deep expertise in Azure SQL performance tuning and OLTP optimization to guarantee sub-second response times for critical applications.

Operational Data Ingestion:

Architect and build resilient pipelines to extract data from vendor APIs/SFTP and load it into Azure SQL with minimal latency

ODS Schema Design:

Design and maintain a normalized (3NF) database model optimized for OLTP and application integration, rather than analytical reporting

Application Integration Layer:

Create and optimize Views, Stored Procedures, and Table Functions that allow internal applications to safely read/write data without direct access to raw tables

High Availability & Sync:

Implement strategies to ensure the internal ODS matches the vendor "State of Truth," handling record updates, deletions, and conflict resolution Performance Tuning (OLTP): Aggressively tune Azure SQL for application performance (index tuning, locking/blocking reduction, query plan analysis) to ensure sub-second response times for integrated apps

Resilience Engineering:

Build "self-healing" mechanisms to queue and retry requests when vendor systems fail, preventing downstream application crashes