VP Cloud Data Analytics Architecture

GM Financial•Arlington, TX

1d•Hybrid

About The Position

GM Financial is undergoing a significant technological modernization, aiming to transform the auto finance industry with a startup-like mindset within a stable, growing public company. They are deeply data-driven, using insights to achieve business objectives and support their mission of zero emission, zero collision, zero congestion, and zero friction. The company is expanding globally with platforms in LATAM, Europe, and China, and is seeking a high-performing leader to scale its Data and Analytics organization. This role is part of a fin-tech culture within a Blue-Chip company, focused on leveraging technology to enhance customer and business support.

Requirements

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 the regulatory landscape for financial institutions.
Expert knowledge of cloud data architecture, data operations, data engineering, full stack (DevOps, Data DevOps, and DevSecOps) 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.
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.
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.
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.

Nice To Haves

R, Ruby, Java and C is preferred.
Open-Source Tools in Azure, AWS and/or Google Cloud is required.
Master’s Degree preferred.

Responsibilities

Lead and direct the Enterprise Cloud Data Analytics Architecture, tools, and platforms teams.
Work with the business to gather data and analytical requirements.
Design, develop, and deploy Enterprise Cloud Data solutions.
Integrate data from disparate sources into cloud, hybrid, and multi-cloud environments.
Design, develop, and monitor processes for data transfer between cloud systems and external vendors.
Collaborate with technical leaders to define API-first, web services, and event-based processes for data accuracy, lineage, metadata, integrity, and efficiency.
Provide data modeling standards, frameworks, and templates to support the business.
Organize, catalog, and define enterprise data for AI, Machine Learning, Data Science, and Reporting.
Scale the Data and Analytics organization globally.
Build, grow, and manage an Agile team of AI, Machine Learning, and Analytics Architects and Full Stack Data Engineers.
Deliver high-quality data and analytics solutions, data DevOps, data DevSecOps, data integrations, and API development.
Ensure the cloud, data, Machine Learning, and AI platform is scalable and secure.
Interact with all levels of leadership to plan and execute work.
Collaborate with broader cross-functional teams to deliver mission-critical projects.
Build partnerships with leaders, team members, and vendors to scale global data and analytics capabilities.
Promote team diversity, equity, and inclusion.
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 to make strategic decisions.
Translate broad strategies into specific action plans.
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, master data layer, 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.
Establish consistent metrics to measure data quality 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.
Assist Senior Vice President in determining the annual business plan and setting 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.