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Full-time
high school, bachelor degree, postgraduate degree
401k matching, Bonding leave for new parents, Tuition assistance, Training, GM employee auto discount, Community service pay
Posted 23d ago
~40 hrs/week
Responsibilities
This role leads the Enterprise Cloud Data Analytics Architecture team in designing, deploying, and managing global cloud data solutions. The VP will scale the data organization while collaborating with business stakeholders to support AI, machine learning, and advanced analytics initiatives.
Requirements
Candidates must have over 10 years of experience in enterprise-scale cloud architecture, data engineering, and leadership of technical teams. Expert proficiency in Azure data services, Python, SQL, and data integration methodologies is required.
Full job description
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.
Responsibilities
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
Qualifications
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.
Amazing people make amazing products. And together, we build the one for every person, purpose and journey.
Industry
Motor Vehicle Manufacturing
Company size
10,001+ employees
Headquarters
Detroit, Michigan
LinkedIn followers
3,649,376
Total funding
$8.5B
General Motors’ vision is to create a world with Zero Crashes, Zero Emissions and Zero Congestion, and we have committed ourselves to leading the way toward this future. Today, we are in the midst of a transportation revolution, and we have the ambition, the talent and the technology to realize the safer, better and more sustainable world we want. As an open, inclusive company, we’re also creating an environment where everyone feels welcomed and valued for who they are. One team, where all ideas are considered and heard, where everyone can contribute to their fullest potential, with a culture based in respect, integrity, accountability and equality. Our team brings wide-ranging perspectives and experiences to solving the complex transportation challenges of today and tomorrow.
For information on the GM Privacy Statement, please visit http://www.gm.com/privacy-statement.html
Offices: 100 Renaissance Center, Detroit, Michigan 48243, US · P.O. Box 33170, Detroit, Michigan 48232-5170, US · 800 N Glenwood Ave, Pontiac, MI 48340, US · Avenida Americo Vespucio 811, Huechuraba, Santiago Metropolitan 8580000, CL · 500 Wentworth St W, Oshawa, Ontario L1J 6G5, CA
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