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GM Financial · 1 day ago

Data Architect II

4001 Embarcadero, Arlington, TX, 76014, US

Full-time

Hybrid

Entry, Mid Level

2+ years exp

GM Financial is committed to innovation and digital transformation through advanced technologies. The Data Architect II will shape the Enterprise Data Lakehouse and Data Warehouse environments by designing data models, creating ETL specifications, and ensuring high-quality data governance across the organization.

Finance

Comp. & Benefits

No H1B

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

Qualification

Data modelingCloud data experienceData governanceETL designData architectureContinuous improvementCollaborationCommunication

Required

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

Bachelor's degree in a related field or equivalent experience required