Business Data Architect
General Motors
- Location
- Warren, Michigan, United States of America
- Work model
- On-Site
- Level
- Senior
- H-1B history
- 267 approvals (FY2023)
- Posted
- 1d ago
Skills
About this role
Job Description
The Role The Business Data Architect serves as the organization’s data governor, thought leader, and subject-matter expert, driving continuous improvement in the quality, efficiency, control, and business use of the team’s data across its lifecycle. In this role, you will have the autonomy to help design and develop a new data environments that empowers Field Teams, Dealers, and Senior Leadership with insights that improve dealer network decision-making, operational performance, and sales outcomes for GM. The successful candidate will be assertive, self-starting, highly collaborative, and effective at translating business needs into practical data architecture, governance, and control solutions.
What You'll Do
(Responsibilities) Develop and own the data governance framework in partnership with business, legal, and technology teams. Define and maintain data governance policies, standards, and procedures aligned with security, privacy, and regulatory requirements. Lead cross-functional governance councils to align priorities, resolve issues, and drive adoption of data standards. Identify critical data domains and establish clear ownership, stewardship, and accountability models. Maintain an inventory of Sales Support data sources and ensure proper security, access, and usage controls. Design and evolve data architecture, models, and shared reporting structures to support business, analytics, and operational needs. Define and manage metadata, business definitions, and data rules in glossaries, catalogs, and related repositories. Document end-to-end data flows, including sourcing, transformations, storage, usage, and ownership. Establish controls, monitoring, and data quality metrics/dashboards to ensure accurate, timely, and consistent data. Partner with business and technology teams to design controls, remediate data quality issues, and drive sustainable process improvements. Optimize and support data governance, data quality, MDM, access management, and related enabling technologies. Design and implement a data operating model (roles, RACI, workflows, change management, issue management). Liaise with Legal/Public Policy to keep governance practices aligned with changing regulatory requirements. Respond to Sales Support data inquiries and guide stakeholders on data availability, lineage, definitions, and proper use. Maintain documentation of processes, standards, and governance decisions; conduct periodic audits of dealer data usage and access. Educate and coach data owners and users through training and communications, acting as a trusted advisor to leadership on data governance for major initiatives. Continuously improve governance processes, tools, and practices to boost efficiency, adoption, data quality, and business value. Your Skills & Abilities (Required Qualifications) Bachelor’s degree required; technical fields (IT, Engineering, Math/Statistics, Information Systems/Data Management) strongly preferred. Equivalent professional experience considered. 5–8+ years of relevant experience, ideally in data governance, master data management, or similar roles. 5+ years of data modeling experience and strong proficiency with relational/NoSQL databases (e.g., Postgres, Oracle) and advanced SQL. Experience with modern data platforms, data hubs/warehouses, and reporting/analytics or enterprise data environments. Hands-on experience with data profiling, cleansing, and defining / applying data quality rules. Proven ability to translate business requirements into practical data models, governance requirements, and solution designs. Strong track record leading cross-functional initiatives and influencing senior stakeholders without direct authority. Deep knowledge of data governance, data quality, and master data management concepts and best practices. Outstanding communication skills with both technical and non-technical audiences; strong facilitation and stakeholder management. Demonstrated analytical