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Data Modernization Jobs in Michigan (NOW HIRING)

Ohio Health

Sponsor modernization of the data and AI technology landscape and establish operating standards, engineering practices, and support models that strengthen reliability, scalability, and execution ...

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Data Modernization information

What jobs in the US pay 300,000 a year?

In the field of data modernization, senior roles such as Data Science Directors, Chief Data Officers, and Data Engineering Managers can earn $300,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership responsibilities. These positions often require a strong background in data architecture, analytics, and strategic planning, and may include bonuses or stock options that contribute to total compensation.

What is the difference between Data Modernization vs Data Analyst?

AspectData ModernizationData Analyst
Primary FocusUpgrading and transforming data systems and infrastructureAnalyzing data to generate insights and reports
Skills RequiredData architecture, cloud platforms, database managementStatistical analysis, data visualization, SQL
Work EnvironmentIT departments, data engineering teamsBusiness units, analytics teams
CertificationsCloud certifications, data management certificationsData analysis, visualization certifications

Data Modernization involves upgrading data systems and infrastructure to improve efficiency and scalability, often requiring technical expertise in data architecture and cloud platforms. In contrast, Data Analysts focus on interpreting data, creating reports, and providing insights to support business decisions. While both roles work with data, their core responsibilities and skill sets differ significantly.

What jobs make $1,000,000 a year?

In the field of data modernization, high-paying roles such as Chief Data Officer, Data Science Director, or Chief Technology Officer can earn over $1 million annually, especially in large organizations or tech companies. These positions typically require extensive experience, advanced skills in data management, leadership, and strategic planning, along with strong industry reputation and sometimes equity compensation.

What is data modernization?

Data modernization is the process of updating and transforming legacy data systems and infrastructure to more current, scalable, and efficient technologies. It often involves migrating data to cloud platforms, implementing new data management tools, and adopting modern analytics practices to improve data accessibility and decision-making.

What are some common challenges faced by professionals working in Data Modernization projects?

Professionals in Data Modernization often encounter challenges such as integrating legacy systems with modern cloud-based solutions, ensuring data quality during migration, and managing data security and compliance. Additionally, they may need to collaborate closely with cross-functional teams to align business goals with technical requirements. Adaptability and strong communication skills are important, as priorities can shift rapidly in response to evolving business needs and technology updates.

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

To thrive in Data Modernization, you need strong expertise in data architecture, cloud platforms, and data migration, often supported by a degree in computer science or information systems. Familiarity with tools like Azure, AWS, Snowflake, ETL frameworks, and certifications such as AWS Certified Data Analytics or Microsoft Azure Data Engineer are commonly required. Excellent problem-solving, project management, and communication skills help professionals effectively lead transformation initiatives and collaborate with stakeholders. These skills are crucial for ensuring seamless migration, maximizing data value, and driving innovation within organizations.

Which 3 jobs will survive AI?

Data modernization roles such as data engineers, data architects, and database administrators are likely to persist as they require specialized knowledge of data systems, architecture, and security that AI cannot fully replicate. These jobs involve designing, managing, and securing complex data environments, often requiring certifications and hands-on expertise. Skills in data governance, cloud platforms, and programming remain essential for these positions.
What are popular job titles related to Data Modernization jobs in Michigan? For Data Modernization jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Modernization jobs in Michigan look for? The top searched job categories for Data Modernization jobs in Michigan are:
Data Modernization jobs near you
Senior Director, Data Analytics & AI Engineering

Senior Director, Data Analytics & AI Engineering

Ohio Health

Hybrid

Full-time

Posted 11 days ago

OhioHealth rating

7.0

Company rating: 7.0 out of 10

Based on 333 frontline employees who took The Breakroom Quiz

404th of 872 rated healthcare providers

Job description

We are more than a health system. We are a belief system. We believe wellness and sickness are both part of a lifelong partnership, and that everyone could use an expert guide. We work hard, care deeply and reach further to help people uncover their own power to be healthy. We inspire hope. We learn, grow, and achieve more - in our careers and in our communities.

Job Description Summary:

The Senior Director of Data Analytics & AI Engineering leads a major function within OhioHealth's technology organization, providing direction through subordinate managers across data engineering, data science, and data governance.
This role is accountable for strategy, business planning, budgets, staffing, quality, compliance, and delivery outcomes, while partnering with technology, operational, and clinical leaders to modernize platforms, advance AI-enabled capabilities, and ensure data assets support enterprise, operational, and patient care priorities across the system.
*This is a hybrid position in Columbus, OH.

Responsibilities And Duties:

Strategy, Planning, and Portfolio Leadership
Lead execution of the data, analytics, and AI engineering strategy, translating OhioHealth priorities and technology direction into operating plans, investment priorities, and measurable outcomes.
Direct long-range planning, architecture, and resource allocation for enterprise data engineering, data science, and governance capabilities to ensure scalable, secure, and high-performing platforms.
Develop annual business plans, operating objectives, and portfolio priorities aligned to long-term functional strategy, enterprise business needs, and measurable performance expectations.
Operating Model, Team Leadership, and Delivery Execution
Lead the function through subordinate managers and senior leaders across data engineering, data science, and data governance, with accountability for team performance, staffing approaches, operating discipline, and coordinated execution across multiple teams.
Sponsor modernization of the data and AI technology landscape and establish operating standards, engineering practices, and support models that strengthen reliability, scalability, and execution consistency.
Ensure data and AI solutions are implemented, supported, monitored, and continuously improved in ways that enable durable adoption, operational performance, and enterprise value realization.
Enterprise Partnership and Solution Delivery
Partner with Technology Delivery, Data & Analytics, Epic, Digital, Security, and operational leaders to align priorities, implementation sequencing, platform readiness, and delivery expectations.
Partner with business, clinical, and operational stakeholders to define desired outcomes, shape solution priorities, and operationalize data and AI capabilities that improve decision-making, workflows, and performance.
Shape executable roadmaps and guide governance and investment decisions in partnership with enterprise strategy, architecture, finance, and operational leadership.
Governance, Data Trust, and Responsible Use
Ensure strong data quality, integrity, reliability, and stewardship practices across engineering efforts in partnership with governance and platform teams.
Partner with cybersecurity, privacy, and compliance leaders to embed security, regulatory, and responsible use requirements into data, analytics, and AI solutions.
Support enterprise governance, prioritization, and decision forums that promote disciplined use of data assets, clear standards, and consistent execution across the portfolio.
Capability Development and Executive Partnership
Strengthen organizational capability by developing leadership depth, technical expertise, and data and analytics literacy across teams and stakeholder groups.
Serve as a trusted partner to senior leaders, providing clear insight into portfolio priorities, delivery progress, risks, and opportunities to support informed enterprise decision-making.
As a High Reliability Organization (HRO), responsibilities require focus on safety, quality and efficiency in performing job duties.
The job profile provides an overview of responsibilities and duties and is not intended to be an exhaustive list and is subject to change at any time.

Minimum Qualifications:

Master's Degree: Computer and Information Science

Additional Job Description:

MINIMUM QUALIFICATIONS

  • Master's degree (or experience in lieu of) in data related fields like Analytics, Data Science, Computer Science with knowledge of healthcare operations or significant experience in healthcare operations with a quantitative mindset.
  • Strong knowledge of the requirements, risks and opportunities around deploying data science, ML and AI at scale.
  • Strong knowledge and experience in transforming technical landscapes to adapt the needs of the business and to seize the value creation potential of data and data platforms.
  • Proven experience with leading transformational change.
  • Excellent leadership and communication skills, with proficiency across hierarchy and function.

SPECIALIZED KNOWLEDGE

  • Prior experience at data platform modernization and cloud enablement

Work Shift:

Day

Scheduled Weekly Hours :

40

Department

IS Adminlstration

Join us!
... if your passion is to work in a caring environment
... if you believe that learning is a life-long process
... if you strive for excellence and want to be among the best in the healthcare industry

Equal Employment Opportunity

OhioHealth is an equal opportunity employer and fully supports and maintains compliance with all state, federal, and local regulations. OhioHealth does not discriminate against associates or applicants because of race, color, genetic information, religion, sex, sexual orientation, gender identity or expression, age, ancestry, national origin, veteran status, military status, pregnancy, disability, marital status, familial status, or other characteristics protected by law. Equal employment is extended to all person in all aspects of the associate-employer relationship including recruitment, hiring, training, promotion, transfer, compensation, discipline, reduction in staff, termination, assignment of benefits, and any other term or condition of employment 

What OhioHealth employees say

Pay

Benefits

Hours and flexibility

Workplace

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About OhioHealth

Sourced by ZipRecruiter

OhioHealth is a not-for-profit, faith-based health system based in Columbus, Ohio, US. Operating since 1981, it is one of the largest and most comprehensive health systems in its area of operation. OhioHealth's business is grounded at the union of the healthcare and medical industry. The organization provides a full range of healthcare services from acute hospital care to rehabilitative and long-term care, including medical research and development.

Industry

Hospitals and health care and social assistance

Company size

10,000+ Employees

Headquarters location

Columbus, OH, US

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