VP Cloud Data Analytics Architecture

Why GM Financial Technology?

GM Financial is set to change the auto finance industry and is leading the path with embarking on tech modernization – we have a startup mindset, preserve our small company culture, in a public company environment with financial stability and intense growth over a decade long history. We are data junkies and trust in data and insights to advance our business objectives.

We take our goal of zero emission, zero collision, zero congestion and zero friction very seriously. We believe as the auto finance market leader we are in the driver seat to lead us in the GM EV mission to change the world. We are building global platforms, LATAM, Europe, China – our high performing talent needs a high performing leader. GMF is comprised of over 10,000 team members globally. Join our fin-tech culture within a Blue-Chip company where we are changing the way we use technology to support our customer and business.

About The Role:

This VP Cloud Data Analytics Architecture is responsible for the leadership and direction of the Enterprise Cloud Data Analytics Architecture, tools and platforms teams. This team will 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. This leader will scale the Data and Analytics organization globally. The VP will build, grow and manage an Agile team of AI, Machine Learning and Analytics Architects and Full Stack Data Engineers. The VP will have significant hands-on as well as leadership experience in data architecture to support Advanced Analytics in Azure, Databricks, APIs, microservices, and event driven architecture. The VP will be responsible for delivering high quality data and analytics solutions, data devops, data dev secops, data integrations, and API development. The VP will ensure the cloud, data, Machine Learning and AI platform is scalable and secure to meet future growth and requirements of business domains. The VP will interact with all levels of leadership to effectively plan/execute work and collaborate with broader cross-functional teams to successfully deliver mission-critical projects. The VP will build partnerships with other leaders, team members, and vendors to scale the global data and analytics capabilities across the enterprise. The VP will promote team diversity, equity and inclusion to support and enhance the Company's culture.

In this role you will:

• Understand, commit to and communicate the Company's vision, goals and strategies
• Build the data and analytics platform to support Company's vision, goals and strategies
• Lead cloud architecture solutions and design for data, machine learning, artificial intelligence and analytics using Azure and Databricks
• Analyze highly complex issues, apply financial analysis and sound judgment and logic to make strategic decisions that balance long and short-term business goals and objectives
• Translate broad strategies into specific actions plans, utilizing existing resources and information to achieve strategic objectives and improve business results
• Collaborate with Leaders to define cloud architecture, business, Digital Transformation and Data & Analytics priorities and goals
• Oversee the department's performance to ensure accountability for achieving business results
• Oversee the data flow from source to target systems
• Oversee the technology landscape of transactional systems, data management and master data layer, to analytics and consuming applications
• Lead and own the relationship with software vendor(s) and service providers supporting data architecture and integration initiatives
• Assess the needs of product/architecture releases with respect to business objectives, security, data dependency, compliance, and timeliness of releases
• Establish consistent metrics to measure quality of data and implemented solutions
• Collaborate with business and technical teams and partners to develop end-to-end Enterprise solutions for data, analytics, machine learning, artificial intelligence in the cloud
• Clearly communicate priorities and monitor the successful and timely completion of department initiatives
• Coach, mentor, and train team members to establish a consistent level of quality, accuracy, accountability and compliance with department standards
• Assist Senior Vice President 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
• Perform other duties as assigned
• Conform with all company policies and procedures

What Makes You an Ideal Candidate?

• Advanced knowledge of cloud data architecture to support modeling, reporting, machine learning, artificial intelligence and analytics
• Advanced knowledge of cloud and data security methodologies, policies, standards and best practices
• Advanced knowledge of best practices in cloud data governance, architecture and tools for regulatory landscape for financial institutions
• Knowledge of GM Financial's core business functions, policies and procedures
• Expert knowledge of cloud data architecture, data operations, data engineering, full stack (dev ops, data dev ops, and dev secops) is required
• In-depth knowledge of cloud data security frameworks is required
• Wide-ranging understanding of general information technology standards and the Company’s systems, such as Provenir, CPW, General Ledger, Oracle ERP, etc.
• Expert knowledge of Azure Data Architecture - Azure Data factory, Azure Data Lake, Microsoft Synapse, Databricks and PySpark utilizing structured and unstructured data
• Expert knowledge of developing data engineering solutions in Python is required
• Expert knowledge of creating cloud MDM, CDC, Data Lineage, Metadata Management solutions is required
• Expert knowledge of utilizing SQL to transform, transport, copy and export data in the cloud is required
• Expert knowledge of developing and optimizing data pipelines from source to target systems is required
• Expert knowledge of transforming and curating multiple data types in Databricks is required
• Expert knowledge of event driven data architecture in the cloud is required
• Expert knowledge of utilizing APIs and web services in the cloud (integrate systems, platforms and data sources) is required
• Extensive experience developing data solutions in the cloud for Marketing, Customer Experience, Data Science, Finance and Treasury is required
• Extensive experience developing one view of the customer data solutions in the cloud (customer360)
• Expert knowledge of industry-standard enterprise data management and integration technologies and methodologies, such as Informatica, is required
• Extensive knowledge of Agile SAFe methodologies and the software development life cycle is required
• Advanced working knowledge of information systems and operations is required
• Extensive experience working with transactional, temporal, time series, and structured and unstructured data in the cloud is required
• Advanced experience with data visualization concepts and tools
• Advanced experience with cloud-based open-source tools, processes and technology for finance companies
• Advanced written and verbal presentation skills with an ability to communicate complex technology, architecture, tools, processes and solutions with senior management
• Ability to interact collaboratively with internal customers and external vendors on highly complex enterprise cloud data and platform strategies
• Demonstrated quantitative skills and ability to apply complex cloud data architecture principles
• Demonstrated expertise in leading distributed teams of engineers and architects, as well as executives, to align on key architectural and technical decisions and direction – and guiding those through successful execution. Lead and mentor the cloud data architecture team in tools, processes and technology
• Experience architecting large sophisticated transactional systems with high volume and high-performance requirements in the cloud – Azure, AWS, Google Cloud
• Proven cloud knowledge and deep understanding of Azure services – Azure Data Factory, Service Bus, ADLS2, Delta Lake, Cosmos DB, Synapse
• SAS, R, Ruby, Java and C is preferred
• Open-Source Tools in Azure, AWS and/or Google Cloud is required
• Azure Data, Data Design and Curation required to support Advanced Analytics (Machine Learning, Risk, Artificial Intelligence) is required
• Traditional RDBMS (Oracle, Teradata, DB2) is required
• Using analytical tools, infrastructure and statistical modeling is required
• Expert proficiency in the Microsoft Suite of Tools - Word, PowerPoint and Excel
• Ability to meet expected delivery dates and the tasks necessary to achieve objectives
• Advanced ability to design data solutions to meet needs of the business in the cloud - Azure Data Factory, Cosmos DB, Databricks, PySpark, Synapse
• Advanced ability to develop accurate and efficient data integration processes in the cloud using APIs and microservices
• Advanced ability to design and communicate high level cloud data architecture requirements to support data science, machine learning, marketing, customer experience and artificial intelligence solutions

Additional Knowledge and Skills

Working effectively within an AI enabled environment:

• Ability to use AI tools (e.g., Microsoft Copilot) to support daily work
• Skills in evaluating AI outputs for accuracy, compliance, and bias
• Experience integrating AI into workflows to improve efficiency or insights
• Familiarity with AI assisted research, summarization, and content generation
• Understanding of responsible AI use, including ethics and data protection

Experience & Education:

• 10+ years of experience in building enterprise scale cloud architecture, applications to support machine learning, artificial intelligence and analytics required
• 10+ years of experience with enterprise cloud integrations and custom solutions delivery to support advanced analytics required
• 10+ years of experience with data science and analytics tooling, solution design, integration and delivery in the cloud required
• 7-10 years of experience in managing enterprise cloud data architecture teams required
• 7-10 years of leadership experience required
• High School Diploma or equivalent required
• Bachelor’s Degree in related field or equivalent work experience required
• Master’s Degree preferred

What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.

Our Culture: Our team members define and shape our culture. We have an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than. work — we thrive.

Compensation: Competitive salary and bonus eligibility; this role is eligible for company vehicle program.

Work Life Balance: Flexible hybrid work environment, 3-days a week in office.

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