Data Architect II

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.

The Data Architect II plays a key role in shaping GM Financial' s Enterprise Data Lakehouse and Data Warehouse environments. In this role, you'll design and document logical and physical data models, create ETL design specifications, and ensure high‑quality, well‑governed data across the organization.

You'll help drive our Enterprise Data Strategy by applying data governance standards, collaborating with cross‑functional teams, and communicating design decisions to both technical and non‑technical partners. You'll also own the publication and maintenance of enterprise data models and supporting documentation.

If you're passionate about building scalable, well‑structured data ecosystems and influencing how data is used across the enterprise, this role offers a meaningful opportunity to make an impact.

Please note: We are unable to provide visa sponsorship either now or in the future.

This is a hybrid role- 2 days in office at either Las Colinas or Arlington, TX office, 3 days work from home.

RESPONSIBILITIES

Responsibilities

• Design modern data architectures including Data Lakehouse medallion patterns, Data Lakes, and Data Warehouses; create logical/physical data models using relational, dimensional, and Data Vault techniques.
• Develop scalable cloud data solutions leveraging Databricks Delta Lake, Azure data storage, and multi‑cloud platforms (Snowflake, AWS S3/Redshift); ensure efficient data movement, integration, and storage.
• Analyze and model complex datasets-identify patterns across disparate systems, define data flows, document integration strategies, and create clear diagrams (ERDs, conceptual/data flow diagrams) for technical and non‑technical audiences.
• Apply and uphold data governance standards by maintaining enterprise modeling guidelines, collaborating with business and IT teams, and partnering with developers, SREs, and data engineers to enable high‑quality, data‑driven solutions.
• Support continuous improvement by staying current on emerging data technologies and trends and contributing to innovation across GM Financial; experience with Power BI or similar tools is preferred.

• 2-4 years of data modeling with strong experience designing databases, ETL patterns, and documenting data architecture.
• Hands-on cloud data experience (2-4 years) with Azure preferred, plus exposure to Databricks Delta Lake and multi‑cloud platforms (AWS or GCP).
• Background in enterprise data environments, including transactional and analytical data, data governance, and data administration; experience with Oracle/Exadata or SQL Server is a plus.
• Experience building cloud and DevOps‑enabled data pipelines, using tools such as Databricks Jobs, Kafka, Azure Event Hub, or Service Bus; exposure to ML/advanced analytics deployment is a plus.
• Education: Bachelor's degree in a related field or equivalent experience required; Master's preferred.