Data Engineering Manager Jobs in Michigan
Data Engineering Manager jobs in Michigan are in active demand, concentrated in automotive technology, financial services, healthcare IT, and manufacturing analytics, with openings at every level from team lead through director. Detroit, Grand Rapids, and Ann Arbor account for the bulk of hiring, anchored by major employers like Ford Motor Company, General Motors, and Blue Cross Blue Shield of Michigan. The most sought-after specialties in Michigan are cloud data platform leadership, real-time pipeline architecture, and analytics infrastructure for connected vehicle and supply chain systems. Find a role that fits below and apply directly.
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Who We Are
VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world's leading creative companies, including the WARC Creative 100. VML's global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore.
VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel.
For more information, please visit www.vml.com and follow along on LinkedIn #WeAreVML.
About the Role
We're seeking a Executive Director of Data Engineering to lead the architecture, infrastructure, and engineering standards that power our global marketing intelligence capabilities. Reporting directly to the Chief Marketing Intelligence Officer, this leader will modernize our AI infrastructure, accelerate how we build and deliver, and set global data standards across every domain we touch — creative, CX/site, CRM, audience, and media data. The ideal candidate is a hands-on technologist and a strategic leader who can build best-in-class engineering practices at global scale while driving the move toward agile, automated, and AI-native data delivery.
What You'll Do
AI Infrastructure & Engineering Modernization
- Design and evolve scalable AI and data infrastructure that supports predictive, prescriptive, and generative use cases across the function.
- Establish standards and tooling for accelerated delivery and faster coding — including AI-assisted development, reusable components, and automation that compresses time-to-value.
- Evaluate and introduce new technologies that enable innovation across creative, CX/site, CRM, audience, and media data domains.
- Mature our MLOps and deployment practices so models and data products move from prototype to production reliably and repeatably.
Data Standards, Taxonomies & Governance
- Develop comprehensive, future-proof data taxonomies and data standards that bring consistency and interoperability across domains and regions.
- Set and govern global data standards — architecture, quality, lineage, documentation, and metadata — that scale across the network and agency partners.
- Embed data governance, privacy, and security by design, ensuring compliance with global regulatory requirements (e.g., GDPR, CCPA) and responsible AI practices.
- Create a single, trusted foundation for data that improves accuracy, accessibility, and reuse across teams.
Delivery Excellence & AI Integration
- Drive continuous progress toward agile, automated, and effective data delivery, embedding DevOps/DataOps practices and CI/CD across engineering workflows.
- Define and uphold best-in-class standards for AI integration, from data pipelines through model deployment and monitoring.
- Build and lead a high-performing, globally distributed engineering organization, raising the bar on technical excellence, velocity, and reliability.
- Partner with product, analytics, and agency teams to ensure infrastructure and standards translate into faster, higher-quality outcomes.
What You'll Bring
- 20+ years of experience in data engineering, data architecture, or platform engineering, including senior leadership of global or distributed engineering teams.
- Deep expertise in modern data infrastructure, cloud platforms, and AI/ML engineering, with hands-on command of scalable pipeline and platform design.
- Proven success establishing data taxonomies, standards, and governance frameworks across complex, multi-domain environments.
- Experience modernizing engineering practices toward automation, agile delivery, and AI-assisted development.
- Strong understanding of marketing and media data domains — creative, CX/site, CRM, audience, and media — ideally within automotive, broader industry, or agency/media agency contexts.
- Track record of integrating AI responsibly and at scale, with fluency in MLOps, DataOps, and data governance.
- Exceptional leadership, communication, and stakeholder-management skills at the executive level.
We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we've adopted a hybrid approach, with teams in the office an average of four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.
WPP (VML) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.
When you click "Submit Application", this will send any information you add below to VML. Before you do this, we think it's a good idea to read through our Recruitment Privacy Policy. California residents should read our California Recruitment Privacy Notice. This explains what we do with your personal data when you apply for a role with us, and, how you can update the information you have provided us with or how to remove it.
Who We Are
VML is a global creative company that combines brand experience, customer experience, and commerce to create connected brands that drive growth. Guided by a Human First philosophy, VML is known for its innovative work for brands and consistently ranks among the world's leading creative companies, including the WARC Creative 100. VML's global network spans 55+ markets with principal offices in Buenos Aires, Kansas City, London, New York, São Paulo, Shanghai and Singapore.
VML is part of WPP, the trusted growth partner for the world's leading brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise solutions and expert strategic counsel.
For more information, please visit www.vml.com and follow along on LinkedIn #WeAreVML.
About the Role
We're seeking a Executive Director of Data Engineering to lead the architecture, infrastructure, and engineering standards that power our global marketing intelligence capabilities. Reporting directly to the Chief Marketing Intelligence Officer, this leader will modernize our AI infrastructure, accelerate how we build and deliver, and set global data standards across every domain we touch — creative, CX/site, CRM, audience, and media data. The ideal candidate is a hands-on technologist and a strategic leader who can build best-in-class engineering practices at global scale while driving the move toward agile, automated, and AI-native data delivery.
What You'll Do
AI Infrastructure & Engineering Modernization
- Design and evolve scalable AI and data infrastructure that supports predictive, prescriptive, and generative use cases across the function.
- Establish standards and tooling for accelerated delivery and faster coding — including AI-assisted development, reusable components, and automation that compresses time-to-value.
- Evaluate and introduce new technologies that enable innovation across creative, CX/site, CRM, audience, and media data domains.
- Mature our MLOps and deployment practices so models and data products move from prototype to production reliably and repeatably.
Data Standards, Taxonomies & Governance
- Develop comprehensive, future-proof data taxonomies and data standards that bring consistency and interoperability across domains and regions.
- Set and govern global data standards — architecture, quality, lineage, documentation, and metadata — that scale across the network and agency partners.
- Embed data governance, privacy, and security by design, ensuring compliance with global regulatory requirements (e.g., GDPR, CCPA) and responsible AI practices.
- Create a single, trusted foundation for data that improves accuracy, accessibility, and reuse across teams.
Delivery Excellence & AI Integration
- Drive continuous progress toward agile, automated, and effective data delivery, embedding DevOps/DataOps practices and CI/CD across engineering workflows.
- Define and uphold best-in-class standards for AI integration, from data pipelines through model deployment and monitoring.
- Build and lead a high-performing, globally distributed engineering organization, raising the bar on technical excellence, velocity, and reliability.
- Partner with product, analytics, and agency teams to ensure infrastructure and standards translate into faster, higher-quality outcomes.
What You'll Bring
- 20+ years of experience in data engineering, data architecture, or platform engineering, including senior leadership of global or distributed engineering teams.
- Deep expertise in modern data infrastructure, cloud platforms, and AI/ML engineering, with hands-on command of scalable pipeline and platform design.
- Proven success establishing data taxonomies, standards, and governance frameworks across complex, multi-domain environments.
- Experience modernizing engineering practices toward automation, agile delivery, and AI-assisted development.
- Strong understanding of marketing and media data domains — creative, CX/site, CRM, audience, and media — ideally within automotive, broader industry, or agency/media agency contexts.
- Track record of integrating AI responsibly and at scale, with fluency in MLOps, DataOps, and data governance.
- Exceptional leadership, communication, and stakeholder-management skills at the executive level.
We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we've adopted a hybrid approach, with teams in the office an average of four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.
WPP (VML) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.
When you click "Submit Application", this will send any information you add below to VML. Before you do this, we think it's a good idea to read through our Recruitment Privacy Policy. California residents should read our California Recruitment Privacy Notice. This explains what we do with your personal data when you apply for a role with us, and, how you can update the information you have provided us with or how to remove it.
See All 7 Data Engineering Manager Jobs in Michigan
Find roles in Michigan that match your experience and apply in just a few clicks.
Find Data Engineering Manager JobsData Engineering Manager Jobs by City in Michigan
Where Michigan roles are concentrated, by current openings.
Data Engineering Manager Job Market in Michigan
A snapshot from current Michigan openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
What Michigan Employers Look For
The qualifications that appear most often in data engineering manager jobs across Michigan.
- Bachelor's or master's degree in computer science, data engineering, or a related technical field
- Five or more years of data engineering experience with at least two years in a management role
- Hands-on expertise with cloud platforms such as AWS, Azure, or Google Cloud
- Proven ability to build and lead distributed data engineering teams across multiple projects
- Experience designing scalable data pipelines, warehouses, or lakehouse architectures
- Strong cross-functional collaboration skills with product, analytics, and business stakeholders
Data Engineering Manager Jobs in Michigan: Frequently Asked Questions
How do you become a data engineering manager in Michigan?
Most data engineering managers in Michigan move into the role after several years as senior data engineers, followed by a transition to tech lead or engineering lead. Michigan employers in automotive tech, healthcare IT, and financial services typically look for candidates with a computer science or engineering degree and demonstrable experience leading technical teams. Cloud certifications from AWS, Microsoft Azure, or Google Cloud strengthen candidacy significantly and are increasingly expected at Michigan's largest employers.
Which companies hire data engineering managers in Michigan?
Employers hiring data engineering managers in Michigan right now include TORC Robotics, VML, and REPLY, based on current listings on Migrate Mate as of September 2026. Michigan's automotive, healthcare, and financial services sectors generate steady demand for this role beyond the largest names, including regional insurers, hospital systems, and tier-one automotive suppliers headquartered in Southeast Michigan.
Which Michigan cities have the most data engineering manager jobs?
Detroit, Ann Arbor, and Grand Rapids lead Michigan for data engineering manager openings. Detroit and its surrounding suburbs drive the majority of demand thanks to the concentration of automotive technology companies, large insurers like Blue Cross Blue Shield, and healthcare networks, while Ann Arbor benefits from the University of Michigan's research and tech spinout ecosystem and Grand Rapids draws openings from regional healthcare systems and growing fintech employers.
Are there remote data engineering manager jobs in Michigan?
Yes, and more than most fields. About 80% of data engineering manager openings tied to Michigan are remote or hybrid as of September 2026, reflecting how thoroughly this role operates through cloud tools and digital collaboration platforms. The fully remote share tends to be strongest for roles focused on cloud infrastructure, pipeline architecture, and platform strategy rather than positions requiring close coordination with on-site data center or hardware teams.
How can I get hired as a data engineering manager in Michigan with little or no experience?
The most realistic path is building management experience from a senior data engineer or tech lead role within Michigan organizations, then stepping into a manager title internally. Large Michigan employers in automotive tech and healthcare IT regularly promote from within and offer structured mentorship for technical leads. Building a portfolio of pipeline architecture and team coordination work, earning a cloud platform certification, and targeting Michigan employers known for growing internal talent gives candidates without prior manager titles a concrete edge.
Where can I find and apply to data engineering manager jobs in Michigan?
You can find and apply to data engineering manager jobs in Michigan on Migrate Mate, which lists current Michigan openings updated on an ongoing basis. Search the listings, find the roles that fit your background and goals, and apply directly to the ones that match.
See All 7 Data Engineering Manager Jobs in Michigan
Find roles in Michigan that match your experience and apply in just a few clicks.
Find Data Engineering Manager Jobs