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Vice President Data Engineering Jobs (NOW HIRING)

Fortitude Re

AVP, Data Solutions Engineering

Nashville, TN · Hybrid

$110K - $132K/yr

The Assistant Vice President, Data Solutions Engineering will be responsible for building operational data pipelines and delivering fully documented datasets that account for data integrations. This ...

Fortitude Re

AVP, Data Solutions Engineering

Jersey City, NJ · Hybrid

$119K - $143K/yr

The Assistant Vice President, Data Solutions Engineering will be responsible for building operational data pipelines and delivering fully documented datasets that account for data integrations. This ...

Fortitude Re

AVP, Data Solutions Engineering

Jersey City, NJ · Hybrid

$119K - $143K/yr

The Assistant Vice President, Data Solutions Engineering will be responsible for building operational data pipelines and delivering fully documented datasets that account for data integrations. This ...

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$112.5K

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How much do vice president data engineering jobs pay per year?

As of Jun 8, 2026, the average yearly pay for vice president data engineering in the United States is $215,595.00, according to ZipRecruiter salary data. Most workers in this role earn between $180,000.00 and $232,000.00 per year, depending on experience, location, and employer.

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 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 of 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 of 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.
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What are the most commonly searched types of Data Engineering jobs? The most popular types of Data Engineering jobs are:
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Vice President Data Engineering jobs near you
Infographic showing various Vice President Data Engineering job openings in the United States as of May 2026, with employment types broken down into 6% As Needed, 24% Full Time, 61% Part Time, 3% Temporary, and 6% Contract. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution, with an average salary of $215,595 per year, or $103.7 per hour.

AVP, Data Solutions Engineering

Fortitude Re

Nashville, TN • Hybrid

$110K - $132K/yr

Other

Posted 25 days ago

Job description

The Assistant Vice President, Data Solutions Engineering will be responsible for building operational data pipelines and delivering fully documented datasets that account for data integrations. This role is engaged and aligned with our business partners to understand their needs and build data engineering solutions to address these needs. The role will report to the VP, Data Solutions Engineering.  

This role will be based in our Nashville, TN office on a hybrid basis.

What You Will Do: 

  • Deliver well-architected data solutions in partnership with data platform engineers, data governance, data science, and data analytics/visualization peers. 

  • Partner with business teams to design data solutions with the ability to mentor early career data engineers.  

  • Lead build-out and deployment of data pipelines. 

  • Ensure reliability, scalability and governance of data pipelines. 

What You Will Have: 

  • Bachelor's degree in Math, Computer Science or Engineering. 

  • Minimum experience of seven years in a growing data engineering role, with at least five years in programming (Python) and SQL. 

  • Domain knowledge of Actuarial, Investment and Finance within Insurance/Reinsurance industry is a plus. 

  • Strong understanding of ETL/ELT, APIs, Cloud, data operations.

  • Robust knowledge of data lakes, data governance and modern data quality techniques. 

  • Excellent analytical, problem solving and conceptual skills. 

  • Strong verbal and written skills. 

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