Senior Data Engineer

JOB DESCRIPTION

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.

RESPONSIBILITIES

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

• Expert-level proficiency in Azure SQL or SQL Server, including OLTP design, normalization (3NF), referential integrity, and constraints
• Strong experience with Azure ecosystem for event-driven or micro-batch data movement
• Deep understanding of SQL internals-locking, latches, execution plans, and isolation levels (e.g., Read Committed Snapshot)
• Experience consuming RESTful APIs, handling pagination, rate limiting, and JSON parsing
• Working knowledge of security methodologies, policies, and best practices for financial data
• Ability to troubleshoot and optimize high-volume transactional systems for performance and reliability

• 6-8 years of hands-on experience with data engineering required
• High School Diploma or equivalent required
• Bachelor's Degree in related field or equivalent work experience required

• Experience building DR (Disaster Recovery) hot/warm sites for financial data
• Familiarity with Change Data Capture (CDC) tools to minimize payload size
• Experience with FIS or similar financial systems