AVP Cloud Data Analytics Architecture

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Job description

Overview:
Why GM Financial Technology?

GM Financial is set to change the auto finance industry and is leading the path of embarking on tech modernization - we have a startup mindset, and preserve our small company culture, in a public company environment with financial stability and intense growth over a decade-plus 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 an auto finance market leader we are in the driver's seat to lead us in the GM EV mission to change the world.

We are building global platforms, in LATAM, Europe, China, U.S. and Canada - and we are looking to grow our high-performing team. GMF is comprised of over 10,000 team members globally. Join our fintech culture within a Blue-Chip company where we are changing the way we use technology to support our customers, dealers, and business.

Responsibilities:
About the Role:

This AVP Cloud Data Analytics Architecture will lead the cloud data architecture team and help scale the Data and Analytics organization globally. 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. The AVP will ensure the data and analytics platform is scalable and secure to meet our future growth and requirements of business domains. The AVP will have a passion for building agile teams that effectively plan/execute work and collaborate with broader cross-functional teams to successfully deliver mission-critical projects. The AVP will build partnerships with other cloud data architects, cloud architects, team members, and vendors to scale our global data and analytics architecture and capabilities across the enterprise.

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

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

Interact with software vendor(s), data and service providers supporting data architecture and integration initiatives in the cloud

Collaborate with VP Cloud Data Analytics Architecture 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 cloud data architecture 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

Perform other duties as assigned

Conform with all company policies and procedures

Qualifications:
What makes you a dream candidate?

Advanced knowledge of cloud data architecture to support modeling, reporting, machine learning, articial 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

Advanced 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

Advanced knowledge of Azure Data Architecture - Azure Data factory, Azure Data Lake, Microsoft Synapse, Databricks and PySpark utilizing structured and unstructured data

Knowledge of developing data engineering solutions in Python is required

Knowledge of creating cloud MDM, CDC, Data Lineage, Metadata Managemen solutions is required

Knowledge of utilizing SQL to transform, transport, copy and export data in the cloud is required

Knowledge of developing and optimizing data pipelines from source to target systems is required

Knowledge of transforming and curating mulitiple data types in Databricks is required

Knowledge of event driven data architecture in the cloud is required

Knowledge of utilizing APIs and web services in the cloud (integrate systems, platforms and data sources) is required

Experience developing data solutions in the cloud for Marketing, Customer Experience, Data Science, Finance and Treasury is required

Experience developing cloud data domains, such as customer360

Knowledge of industry-standard enterprise data management and integration technologies and methodologies, such as Informatica, is required

Knowledge of Agile SAFe methodologies and the software development life cycle is required

Advanced working knowledge of information systems and operations is required

Experience working with transactional, temporal, time series, structured and unstructured data in the cloud is required

Experience with large-scale enterprise-wide migration of workloads to the cloud required

Effective 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 ability to effectively lead, motivate, challenge, organize and supervise a team of data architects and full stack engineers

Demonstrated quantitative skills and ability to apply complex cloud data architecture principles

Demonstrated expertise in leading distributed teams of engineers and architects to align on key architectural and technical decisions and direction - and guiding those through successful execution

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

Ability to orchestrate, lead, and influence teams, ensuring successful implementation of cloud data projects

SAS, R, Ruby, Java and C is preferred

Open-Source Tools in a 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

Experience:

Bachelor's Degree in related field or equivalent work experience required

Master's Degree in related field preferred

7-10 years experience in building enterprise scale cloud data architecture and applications to support machine learning, artificial intelligence and analytics required

7-10 years of cloud application development solutions, PaaS, SaaS, IaaS, Serverless, Data Orchestration, API Management required
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