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Vice President Data Engineering Jobs in Ohio (NOW HIRING)

Hillenbrand

Vice President, Data & Analytics

Columbus, OH · On-site +1

$173K - $224K/yr

The Vice President, Data & Analytics provides executive leadership for the organization's data ... engineering * Expert-level Databricks (or similar technology): Delta Lake internals (MERGE/CDC ...

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 ...

CareSource

AVP, Data Management

Dayton, OH · On-site

$150 - $300/hr

Job Summary The Associate Vice President, Data Management is a senior technology executive responsible for the strategy, architecture, engineering, integration, quality, and operational management of ...

Goosehead

Vice President - Marketing

Westlake, OH

The Vice President of Marketing leads Goosehead's customer-acquisition engine. This is a digital ... CDP, attribution, experimentation, MMM, and BI - including the data contracts with Data Engineering ...

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Vice President Data Engineering information

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 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 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 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 are the most commonly searched types of Data Engineering jobs in Ohio?

The most popular types of Data Engineering jobs in Ohio are:

What are popular job titles related to Vice President Data Engineering jobs in Ohio?

For Vice President Data Engineering jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Vice President Data Engineering jobs in Ohio look for?

The top searched job categories for Vice President Data Engineering jobs in Ohio are:

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, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Director, Data Engineering

Core Specialty

Cincinnati, OH

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 15 days ago

Job description

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We are looking for a Director, Data Engineering, to lead the continued optimization and maturation of our existing large-scale data platform. This is hands-on technical leadership role: roughly 60% of your time will be spent as a working solution architect - improving, rearchitecting, and scaling data pipelines, infrastructure, and models that power the business. The remaining 40% will be focused on strategic alignment, technical direction, and resource management for the Data Engineering team. A key part of the mandate is ensuring the platform remains AI/ML ready as it scales - well modeled and well governed so that advanced analytics teams can reliably and efficiently access high-quality data.

Reporting to the VP-Data Engineering, AI & ML, you will lead a team of Data Engineers - setting the technical execution direction while staying close enough to the architecture and code to guide hard decision, unblock the team, and ensure the platform continues to scale reliably and security as usage and AI/ML initiatives grow.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over work authorization sponsorship now or in the future for this position.

Key Accountabilities/Deliverables:

Solution Architecture & Hands-On Delivery

  • Own the technical evolution of our existing large-scale data platform, identifying and riving improvements to architecture, performance and scalability data volume and complexity use cases grow

  • Act as the lead solution architect for data engineering initiatives

  • Personally design, prototype, and development of frameworks and critical platform components - especially for high-risk/high complexity initiatives

  • Have a forward-thinking posture as it comes to creating an AI/ML ready data platform

  • Participate in the evaluation, selection and implementation of data platform tooling (i.e. - storage, orchestration, compute, streaming)

  • Reinforce existing data observability solutions/standards across pipelines and the platform

  • Diagnose and resolve complex production issues/technical debt across the data platform - partnering directly with other engineers to resolve.

Strategy, Technical Direction & Resource Management

  • Partner with VP-Data Engineering, AI & ML to define and execute the roadmap for a fully optimized and scalable data platform - ensuring alignment to broader company and data strategies including AI/ML readiness assessments

  • Set technical direction and architectural standards for the team by working closely with Enterprise Architecture

  • Manage, mentor, and develop data engineers

  • Participate in resource planning and prioritization across the team's product roadmap - balancing business requests with platform-based initiatives

  • Represent Data Engineering planning, budgeting, and resource management discussions as needed

  • Stay current with emerging trends in data engineering and data platform architecture - brining innovations into continued data maturity for the organization.


Technical Knowledge and Understanding:

Technical Knowledge

  • Deep expertise in data pipeline design, optimization, and distributed data processing architectures with experience identifying and resolving performance and scalability bottlenecks

  • Platforms: Hands on experience with Snowflake or Databricks (experience in an architecture role with these platforms is a plus), Azure Synapse Analytics/MS Fabric

  • Strong knowledge of cloud data platforms (AWS, Azure, or GCP) and modern data warehouse/Lakehouse architectures (Delta Lake, Iceberg)

  • Working familiarity with AI/ML data requirements and tooling to support AI/ML enablement

  • Strong working proficiency with at least two programming languages (Python, Scala, SQL)

  • Solid understanding of data governance, security, and compliance practices in a regulated or enterprise environment

  • Experience with IAC and CI/CD practices for data systems (i.e. Terraform, GitHub Actions)

Leadership & Soft Skills

  • Proven ability to set technical direction while remaining hands-on and credible at the architecture and code level

  • Strong stakeholder management skills - the ability to translate between technical and non-technical audiences

  • Excellent prioritization and resource management skills across competing technical and business demands

  • A coaching mindset with genuine investment in growing the technical and soft skills of direct reports


Requirements:

  • Bachelor Degree in Computer Science or related field or equivalent work experience.

  • 10+ years experience in data engineering with significant experience in optimizing, scaling, and evolving large-scale mature data platforms

  • 3+ years in an architect role (Solution, Enterprise, Data, Platform) with direct ownership of solution designs

  • 3+ years in a leadership role managing data engineering teams - including direct people management responsibilities

  • Working knowledge of how data platforms enable AI/ML solutions

  • Track record of balancing hands-on technical delivery with people leadership and strategic planning

Nice to Have

  • Experience designing or implementing Agentic workflows for data engineering

  • Experience working with Property & Casualty insurance carriers

  • Experience with Data Vault 2.0 or Ensemble data modeling techniques


#LI-Hybrid

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At Core Specialty, you will receive a competitive salary and opportunities for professional development and advancement. We offer medical, dental, vision, and life insurances; short and long-term disability; a Company-match of 100% of a 6% contribution 401(k) plan; an Employee Assistance Plan; Health Savings Account, Flexible Spending Account, Health Reimbursement Account, and a wellness program

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