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Vice President Data Engineering Jobs in Ohio (NOW HIRING)

Premier Health

VP-DATA/ANALYTICS & AI

Dayton, OH · On-site

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven ...

Premier Health

VP-DATA/ANALYTICS & AI

Dayton, OH · On-site

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven ...

Premier Health

VP-DATA/ANALYTICS & AI

Dayton, OH · On-site

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven ...

Premier Health

VP-DATA/ANALYTICS & AI

Dayton, OH · On-site

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven ...

Premier Health

VP-DATA/ANALYTICS & AI

Dayton, OH · On-site

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven ...

Bread Financial

VP Cloud Platform Engineering

Columbus, OH

$173K - $224K/yr

The VP partners with executive leaders across engineering, architecture, cybersecurity, operations, data, product, and business functions to align platform investments with strategic business ...

Search Connections

VP of Operations

Columbus, OH · On-site

$186K - $225K/yr

The Vice President of Operations is responsible for leading, directing, and overseeing the ... Bachelor's Degree in Business, or engineering preferred, or equivalent in relevant experience * A ...

Dayton Live

VP - Education

Dayton, OH · On-site

Purpose: The Vice President - Education will serve as department leader for all Education ... Contributing to the programming of the Discovery Series, as well as Family programming in ...

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Vice President Data Engineering information

What is the difference between Vice President Data Engineering vs Data Engineering Manager?

AspectVice President Data EngineeringData Engineering Manager
ResponsibilitiesStrategic leadership, overseeing data infrastructure, setting visionTeam management, project execution, technical oversight
Required CredentialsBachelor's/Master's in CS, extensive experience, leadership skillsBachelor's/Master's in CS, technical expertise, management experience
Work EnvironmentExecutive-level, cross-departmental collaborationTeam-based, project-focused, technical environment
Industry UsageCommon in large organizations, strategic rolesWidespread across companies, operational roles

The Vice President Data Engineering focuses on strategic leadership and long-term vision for data infrastructure, while the Data Engineering Manager handles day-to-day team management and project execution. Both roles require strong technical backgrounds, but the VP role emphasizes leadership and strategy, whereas the manager role is more hands-on with technical implementation.

What is a vice president data engineering?

A Vice President of Data Engineering is a senior executive responsible for leading and overseeing the data engineering function within an organization. They manage teams that design, build, and maintain data architectures, pipelines, and infrastructure to support data analytics and business intelligence. The VP of Data Engineering collaborates closely with other executives to define data strategy, ensure data quality, and enable data-driven decision-making across the company. Their role often includes setting technical direction, managing budgets, and ensuring compliance with data governance and security standards.

What are the key skills and qualifications needed to thrive as a vice president data engineering, and why are they important?

To thrive as a Vice President of Data Engineering, you need deep expertise in data architecture, large-scale data systems, and team leadership, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (like AWS, Azure, or Google Cloud), big data technologies (such as Hadoop, Spark), and relevant certifications (e.g., AWS Certified Data Analytics) is highly valued. Strategic thinking, strong communication, and the ability to mentor and motivate teams are crucial soft skills for success in this executive role. These skills and qualities are essential to drive data strategy, ensure robust system performance, and align engineering efforts with business objectives.

What are some common challenges faced by a vice president data engineering, and how can they be addressed?

A Vice President of Data Engineering often deals with challenges such as aligning data strategy with business goals, managing cross-functional teams, and ensuring data quality and security at scale. Balancing rapid innovation with system reliability can also be demanding, as can integrating new technologies with legacy systems. Success in this role typically involves strong communication with stakeholders, fostering a culture of collaboration, and investing in ongoing staff development to keep pace with evolving data landscapes.
What are the most commonly searched types of Data Engineering jobs in Ohio? The most popular types of Data Engineering jobs in Ohio are:
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What cities in Ohio are hiring for Vice President Data Engineering jobs? Cities in Ohio with the most Vice President Data Engineering job openings:
Vice President Data Engineering jobs near you
Infographic showing various Vice President Data Engineering job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

VP-DATA/ANALYTICS & AI

Premier Health

Dayton, OH • On-site

Other

Posted 8 days ago

Job description

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven culture, and ensure effective governance and use of Premier's data assets and ecosystem. Reporting to the Chief Digital Information Officer (CDIO), the VP of Data, Analytics and AI leads the execution of Premier's enterprise data, analytics, and AI strategy and operating model, builds executive and Board-level trust in data as a strategic asset; operationalizes enterprise data governance in partnership with security, privacy, risk, and compliance leaders; and develops the talent and culture required to mature Premier's data and analytics capability.  This role will partner with senior leaders across Premier Health to understand their data needs and deliver tools to enable them to achieve their business, clinical and operational initiatives.

As a member of the DHT senior leadership team, the VP of Data, Analytics and AI leads day-to-day strategy execution, operating model design, and delivery for the data, analytics, and AI portfolio.  This role will work in close coordination with the CDIO's technology infrastructure, Epic platform governance, and cybersecurity functions to ensure a single, unified digital agenda to support the strategic initiatives of Premier Health.  The VP of Data, Analytics and AI also plays a leading role in building data governance and analytics infrastructure supporting Premier's Wright State University academic partnership and Academic Medical Center designation, consistent with priorities set by the organization.

Education: Bachelor's Degree in Business Administration, Computer Science, Data Science, Information Systems, Health Informatics, or a related field. Master's degree (e.g., MBA, MS Data Science, MS Health Informatics) preferred.

Licensure/Certification/Registration: None required; Certified Analytics Professional (CAP) or comparable data/AI governance certification preferred.

Experience: Minimum 10 to 15 years of progressive business experience, recently at or near the executive level such as Senior data, analytics, or business intelligence executive (e.g., VP/SVP Data & Analytics, Chief Analytics Officer, Chief AI Officer) with progressive leadership experience required. Must have experience with enterprise data & analytics strategy, data governance, AI enablement, and cross-functional program leadership. Preferred experience: Healthcare or health system experience; academic medical center or university-affiliated data governance experience; strategy or management consulting background.
Other experience requirements: 5 or more years of progressive leadership managing cross-functional, multidisciplinary data and analytics teams across a complex organization.

Knowledge/Skills:
      Enterprise data, analytics, and AI strategy development and execution, including policy development
      Data and analytics governance (master data management, data quality, data stewardship) and connected governance with privacy, security, and compliance functions
      Broad understanding of information architectures (data fabric, data mesh, data warehouse, data lake, data hub) and analytics approaches (descriptive, diagnostic, predictive, prescriptive)
      AI fundamentals, including AI-ready data practices, responsible/ethical AI use, and awareness of applicable healthcare regulations (e.g., HIPAA, information blocking rules, emerging state and federal AI regulation)
      Business and financial acumen; ability to translate data, analytics, and AI concepts into business and clinical outcomes and ROI
      Exceptional executive communication, storytelling, and stakeholder influence across clinical, operational, financial, and Board audiences
      Demonstrated leadership building and managing complex, multidisciplinary teams and driving enterprise-wide culture change
      Experience operating within a CIO/CDIO-led digital governance structure, and partnering effectively with CISO, Compliance, and Legal functions on data trust, security, and governance
      Statistical literacy (e.g., understanding the difference between correlation and causation) sufficient to guide analytically rigorous decision-making

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