AVP Cloud Data Analytics Architecture

Why GM Financial 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.

About the role: 

This AVP Cloud Data Analytics Architecture will lead the cloud data architecture team and help scale the Data and Analytics organization for various finance groups.  As an experienced cloud data architect, this role work with the business to gather data and analytical requirements; design, develop and deploy Enterprise Cloud Data solutions; integrate data from disparate sources to load to the cloud, hybrid and multi-cloud; design, develop and monitor processes to transfer data between cloud systems and/or external vendors; collaborate with technical leaders to define api-first, web services, event based processes to maintain accuracy, lineage, metadata, integrity and efficiency of data across multiple levels of curation and consumption; provide data modeling standards, frameworks and templates to support the business; organize, catalog and define enterprise data to support AI, Machine Learning, Data Science and Reporting.  The AVP will have hands-on experience in cloud data architecture to support Advanced Analytics in Azure, Databricks, APIs, microservices, and event driven architecture. The AVP will ensure the cloud, data, Machine Learning and AI platform is scalable and secure to meet future growth and requirements of business domains. This AVP will lead the strategy, development, and delivery of Finance data assets within the Finance Center of Excellence (COE), while managing a team of data engineers responsible for data engineering, analysis and reporting. The role is accountable for driving the data engineering roadmap, implementing process improvements, and delivering scalable SQL-based reporting and data solutions. 

In this role, you will:

• Architect the data and analytics platform to support Company's vision, goals and strategies
• Develop cloud architecture solutions and design for data, machine learning, artificial intelligence and analytics using Azure, Informatica and Databricks
• Partner with the Finance business teams to design and implement governed, finance‑critical data products—ensuring accuracy, stewardship alignment, and seamless integration with enterprise data engineering standards
• Enable various Finance initiatives by engineering scalable, reliable datasets that support Securitization, FP&A reporting, Oracle Fusion–based workflows, Gen‑AI Finance Assistant use cases, and advanced analytics across Finance
• Translate broad strategies into specific data architecture plans, utilizing existing resources and information to achieve strategic objectives and improve business results
• Collaborate with Data Leadership to define cloud data architecture, business, Digital Transformation and Data & Analytics priorities and goals+++
• Collaborate with VP Cloud Data Analytics Architecture on department's performance to ensure accountability for achieving business results
• Architect the flow of data from transactional systems, data management and master data layer, to the cloud data and analytics platform and consuming applications
• Collaborate with various VP across finance groups to define and report the needs of product/architecture releases with respect to business objectives, security, data dependency, compliance, and timeliness of releases
• Architect and develop consistent metrics to measure data quality, security, utilization and consumption for management and audit
• Collaborate with business and technical teams to develop end-to-end Enterprise solutions for data, analytics, machine learning, artificial intelligence in the cloud
• Coach, mentor, and train data engineering team members to establish a consistent level of quality, accuracy, accountability and compliance with department standards
• Assist leadership in determining the annual business plan and setting the budgetary requirements for the department and manage each plan to ensure compliance and completion
• Champion an environment that promotes trust, continuous improvement, innovation, quality outcomes and self-development
• Develop relationships with key customer business and technical decision makers: drive long-term cloud data adoption within the company; enable cloud data advocacy
• Share insights and best practices, and connect with teams to remove key blockers