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Data Enablement Jobs in Michigan (NOW HIRING)

Guardian Alarm

Director, Data Strategy

Southfield, MI · On-site

Establish a multi-year roadmap for data architecture, analytics, business intelligence, governance, AI/ML enablement, and related data capabilities. * Partner with the CTO and business leaders to ...

Guardian-Alarm

Director, Data Strategy

Southfield, MI · On-site

$160 - $240/hr

Analytics, Business Intelligence & Data Enablement * Provide leadership for enterprise analytics, reporting, and business intelligence capabilities that improve organizational decision-making.

Guardian Alarm

Director, Data Strategy

Southfield, MI · On-site

$180 - $260/hr

Analytics, Business Intelligence & Data Enablement * Provide leadership for enterprise analytics, reporting, and business intelligence capabilities that improve organizational decision-making.

Huntington

CML Sales Enablement Specialist II

Detroit, MI · On-site +1

$57K - $113K/yr

This is an exciting opportunity to join the fast-paced, Commercial Banking Sales Enablement Team as ... Understand and utilize customer data and market trends to determine value-add needed to attain ...

Huntington

CML Sales Enablement Specialist II

Detroit, MI · On-site +1

$57K - $113K/yr

This is an exciting opportunity to join the fast-paced, Commercial Banking Sales Enablement Team as ... Understand and utilize customer data and market trends to determine value-add needed to attain ...

HTC Global Services

Data & AI Architect

Grand Rapids, MI · On-site

$61.25 - $78.75/hr

AI & Advanced Analytics Enablement * Design data foundations for Machine Learning and Generative AI. * Build feature stores and semantic layers. * Enable real-time analytics and predictive modeling.

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Data Enablement information

What is data enablement?

Data enablement is the process of making data accessible, usable, and valuable across an organization. It involves implementing tools, processes, and strategies that empower employees to access, analyze, and act on data efficiently. The goal of data enablement is to break down data silos, improve data literacy, and support better decision-making by ensuring the right people have the right data at the right time.

How does a data enablement professional typically collaborate with other departments to drive data-driven decision-making?

Data Enablement professionals work closely with departments such as marketing, finance, operations, and IT to ensure that accurate, accessible data informs strategic decisions. They often facilitate data literacy training, help teams define data requirements, and establish efficient data pipelines. Collaboration is key—regular meetings, workshops, and cross-functional projects are common to align data initiatives with business goals. This role also involves translating complex data concepts into actionable insights for non-technical stakeholders, fostering a culture of data-driven decision-making throughout the organization.

What are the key skills and qualifications needed to thrive in data enablement, and why are they important?

To thrive in Data Enablement, you need strong analytical skills, a solid understanding of data management principles, and experience with data governance, often supported by a degree in data science, information technology, or a related field. Familiarity with data visualization tools (such as Tableau or Power BI), data integration platforms, and database systems are commonly required, along with certifications like CDMP (Certified Data Management Professional). Excellent communication, collaboration, and problem-solving skills help you translate data insights into actionable business strategies and foster data literacy across teams. These competencies are crucial for ensuring high-quality, accessible data that drives informed decision-making and organizational growth.

What is the difference between Data Enablement vs Data Analyst?

AspectData EnablementData Analyst
Primary FocusProviding tools, platforms, and infrastructure to empower data usersAnalyzing data to generate insights and reports
Skills & CertificationsData management, platform administration, data governanceStatistical analysis, SQL, data visualization tools
Work EnvironmentIT teams, data platforms, cross-functional teamsBusiness units, analytics teams, reporting environments
Employer & Industry UsageTech companies, large enterprises, data-driven organizationsMarketing, finance, operations departments across industries

Data Enablement focuses on building and maintaining the infrastructure and tools that allow organizations to access and utilize data effectively. In contrast, Data Analysts interpret and analyze data to provide actionable insights. While both roles work with data, Data Enablement is more technical and infrastructure-oriented, whereas Data Analysts are more focused on analysis and reporting.

What job categories do people searching Data Enablement jobs in Michigan look for?

The top searched job categories for Data Enablement jobs in Michigan are:

What cities in Michigan are hiring for Data Enablement jobs?

Cities in Michigan with the most Data Enablement job openings:

Data Enablement jobs near you
Infographic showing various Data Enablement job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Chief Data & AI Officer (CDAO)

University of Michigan

Ann Arbor, MI • On-site

Full-time

Retirement, PTO

Posted 7 days ago

University Of Michigan rating

8.0

Company rating: 8.0 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

189th of 627 rated colleges and universities

Job description

Job Summary
Michigan Medicine is seeking a Chief Data & Artificial Intelligence Officer (CDAO) to provide executive leadership for the enterprise data, analytics, and AI ecosystem, enabling a data-driven, AI-enabled academic health system.
Reporting to the Chief Digital & Information Officer (CDIO), the CDAO is accountable for the strategy, governance, architecture, and enablement of data and AI capabilities across Michigan Medicine. This role ensures data is trusted, accessible, governed, and translated into actionable intelligence, while enabling scalable, responsible adoption of artificial intelligence.
The CDAO plays a central role in supporting Michigan Medicine's evolution into a learning health system, orchestrating data and AI capabilities across clinical, operational, academic, and research domains. The role emphasizes platform enablement over centralization, fostering a distributed analytics and democratized AI model supported by strong governance, shared standards, and modern tooling.
Organizational Scope
The CDAO provides enterprise leadership across core domains including:
  • Enterprise Data Strategy & Governance
  • Data Platforms, Architecture & Engineering
  • Clinical & Operational Analytics (including Epic Cogito)
  • Artificial Intelligence & Advanced Analytics (AI/ML/GenAI)
  • Machine Learning Operations (MLOps) & AI Lifecycle Management
  • Data Literacy, Self-Service Analytics & AI Enablement
  • Data Infrastructure & Data Use Enablement
  • AI Governance, Ethics & Responsible AI
  • AI Orchestration, Automation, and Agentic Monitoring

Responsibilities*
Key Responsibilities
Enterprise Data & AI Strategy
  • Define and execute a comprehensive enterprise data and AI strategy aligned with Michigan Medicine's clinical, operational, academic, and research priorities.
  • Position Michigan Medicine as a leader in AI-enabled healthcare delivery, academia, research, and operations.
  • Serve as the executive advisor on data, analytics, and AI investments, opportunities, and risks.

Data Governance, Strategy & Stewardship (Enterprise Ownership)
  • Partnering across the enterprise, establish and lead enterprise data governance, including:
    • Data ownership and stewardship models
    • Data policies, standards, and controls
    • Data quality, integrity, and trust frameworks
  • Define and enforce data management standards, including:
    • Metadata, cataloging, and lineage
    • Data classification and access controls
    • Master and reference data strategies
  • Ensure all data assets are secure, compliant, governed, and usable at scale.

Data Platforms, Architecture & Infrastructure
  • Lead enterprise data platform strategy and delivery, including:
    • Data architecture and engineering
    • Data pipelines, integration, and interoperability
    • Scalable data environments supporting clinical, administrative, academic, and research workloads
  • Oversee clinical data infrastructure and architecture, enabling:
    • Longitudinal patient records
    • Master Data Management
    • Interoperability across systems and partners
    • Support for advanced analytics and AI
  • Lead and optimize the Epic Cogito environment, ensuring it is:
    • Integrated into the broader enterprise data ecosystem
    • Performing, scalable, and aligned with reporting and analytics needs
  • Partner with the CTO to ensure alignment between:
    • Data platforms
    • Underlying infrastructure and cloud environments
    • Integration and interoperability platforms (API management, middleware)

Analytics & Data Enablement (Distributed Model)
  • Enable a distributed analytics model by:
    • Providing shared platforms, tools, and governed access
    • Supporting domain-based analytics across clinical, operational, academic, and research teams
  • Lead enterprise analytics capabilities, including:
    • Clinical, operational, and financial analytics
    • Revenue cycle, administrative, and performance analytics
    • Research and academic analytics
    • Self-service BI tools and reporting environments
  • Promote data democratization, ensuring users can:
    • Access trusted data
    • Build insights independently
    • Operate within governance guardrails

Artificial Intelligence & Advanced Analytics
  • Lead enterprise AI strategy, including:
    • Predictive analytics
    • Machine learning and deep learning
    • Generative AI and agent-based systems
  • Identify, prioritize, and scale high-impact AI use cases across clinical, operational, and research domains.
  • Partner with CHIO to enable clinical decision support and AI in care delivery.
  • Partner with CAO to embed AI into applications and workflows.

MLOps, AI Orchestration & Agentic Monitoring
  • Establish and lead Machine Learning Operations (MLOps) capabilities, including:
    • Model development pipelines
    • Deployment, monitoring, and lifecycle management
    • Model versioning, retraining, and performance tracking
  • Implement enterprise capabilities for:
    • AI orchestration across systems and workflows
    • Agentic AI management and monitoring
    • Continuous validation of model performance, drift, and bias
  • Ensure AI is:
    • Scalable and production-ready
    • Continuously monitored and improved
    • Integrated into enterprise workflows

AI Governance, Ethics & Responsible Use
  • Establish enterprise frameworks for AI governance and ethical use, including:
    • Model transparency and explainability
    • Bias detection and mitigation
    • Accountability and oversight
  • Partner with legal, compliance, and clinical leadership to ensure:
    • Responsible AI deployment
    • Regulatory alignment
    • Patient safety and trust

Data Literacy, AI Enablement & Innovation
  • Promote a culture of data literacy and AI fluency across the organization.
  • Establish enterprise capabilities for:
    • Training, enablement, and adoption
    • Self-service analytics and AI tools
    • Innovation sandboxes and experimentation environments
  • Enable "vibe coding" and democratized AI experimentation in a controlled, governed environment.

Cross-Functional Leadership & Integration
  • Partner with:
    • Application leaders - embed data and AI into applications
    • Technology leaders - align data and infrastructure platforms
    • Customer Experience - drive adoption of analytics and AI tools
    • Health Informatics - align AI and analytics to clinical workflows
    • Academics and Research - enable research data, advanced analytics, and AI
    • Enterprise Delivery - integrate data/AI into portfolio prioritization and execution

Financial, Vendor & Workforce Leadership
  • Lead investment planning and financial management for data and AI capabilities.
  • Manage relationships with vendors and platform providers in data, analytics, and AI.
  • Build and lead high-performing teams across:
    • Data engineering and architecture
    • Analytics and BI
    • AI/ML engineering
    • Governance and enablement

Required Qualifications*
  • Bachelor's degree in Data Science, Computer Science, Informatics, Engineering, or related field.
  • 15+ years of experience in data, analytics, and/or AI leadership roles.
    • 10+ years of leadership experience managing large, multidisciplinary teams.
  • Demonstrated experience building and scaling enterprise data platforms and AI capabilities.
  • Deep expertise in:
    • Data architecture and engineering
    • Analytics and BI
    • AI/ML and modern data ecosystems
  • Proven ability to operate in complex, federated, healthcare or academic environments.

Desired Qualifications*
  • Master's or PhD in Data Science, Informatics, Computer Science, Engineering, or related discipline.
  • Experience in an academic medical center, health system, or research environment.
  • Experience with Epic Cogito and healthcare data ecosystems.
  • Track record of deploying AI at scale in research, academic, operational or clinical settings.

Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .
Additional Information
Benefits Information
We offer a benefits package that includes comprehensive training and career development opportunities, generous retirement savings plans, ample paid time off, and a wealth of family care support: https://careers.umich.edu/benefits/
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Detail
Job Opening ID
281965
Working Title
Chief Data & AI Officer (CDAO)
Job Title
Chief Data & AI Officer Hlth
Work Location
Michigan Medicine - Ann Arbor
Ann Arbor, MI
Modes of Work
Hybrid
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
Exec Vp Med Affairs
Department
MM HITS OCIO Administration
Posting Begin/End Date
8/24/2026 - 8/31/2026
Career Interest
Information Technology

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About University of Michigan

Sourced by ZipRecruiter

The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Ann Arbor, MI, US

Year founded

1817

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