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Vice President Data Engineering Jobs (NOW HIRING)

Happen Bank

VP, Data Platforms

San Francisco, CA · On-site

The VP, Data Platforms is responsible for the data platform, infrastructure, governance, and engineering services that power every business at Happen Bank, ensuring secure, scalable, and reliable ...

Trella Health

$173K - $223K/yr

You will partner with product, engineering, clinical, and commercial leadership to ensure data and ... Chief Technology Officer As the VP of Data Strategy at Trella, you will lead: Strategy & Vision

BNY

Vice President, Data Privacy

Pittsburgh, PA · Hybrid

Vice President, Data Privacy At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the ...

BNY

Vice President, Data Privacy

Pittsburgh, PA · On-site

Vice President, Data Privacy At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the ...

LifeMD

VP, Data & Analytics

Manhattan, NY · On-site

$198K - $255K/yr

About the role LifeMD is seeking a visionary and execution-focused Vice President of Data ... This is a hands-on Data engineering leadership role for someone who has successfully taken data and ...

LifeMD

VP, Data & Analytics

Manhattan, NY · On-site

$198K - $255K/yr

About the role LifeMD is seeking a visionary and execution-focused Vice President of Data ... This is a hands-on Data engineering leadership role for someone who has successfully taken data and ...

LifeMD

VP, Data & Analytics

New York, NY · Remote

$196K - $253K/yr

About the role LifeMD is seeking a visionary and execution-focused Vice President of Data ... This is a hands-on Data engineering leadership role for someone who has successfully taken data and ...

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Vice President Data Engineering information

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

As of Jul 19, 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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Vice President Data Engineering jobs near you
VP, Data Platform and Knowledge

VP, Data Platform and Knowledge

Wolfe, LLC

Pittsburgh, PA • On-site

$200K - $226K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 27 days ago

Job description

VP, Data Platform and Knowledge
Department: Data
Employment Type: Full Time
Location: Pittsburgh Onsite
Compensation: $200,000 - $226,000 / year
Description
Wolfe is building the data and knowledge foundation that every AI-powered product, team, and decision in the company will run on and we're looking for a VP-level leader to own it. As VP of Data Platform & Knowledge, you will set the strategic direction for how Wolfe ingests, governs, structures, and surfaces information at scale. This is an executive-level, high-trust role at the intersection of data engineering, knowledge architecture, and AI infrastructure one that sits at the center of Wolfe's long-term competitive advantage.
You will work directly with the C-suite and cross-functional leadership to make our data trustworthy, our AI teams self-sufficient, and our platform ready to grow as fast as the business demands. You'll bring a founder's sense of urgency and ownership, operating with the authority to make decisions, the accountability to deliver outcomes, and the influence to align the entire organization around a shared data standard.
This is not a hands-on engineering role. You will set direction, attract and lead talent, and hold the organization accountable to results.
This is a 5-day onsite role in Pittsburgh, PA.
Responsibilities
  • Own the enterprise-wide data and knowledge platform strategy including ingestion pipelines, governance frameworks, vector databases, and semantic search infrastructure ensuring every layer is production-grade, scalable, and AI-ready.
  • Define, enforce, and evangelize data quality and governance standards that operate by default, not by committee, eliminating friction for AI and engineering teams building on the platform.
  • Serve as a key executive stakeholder across AI product, engineering, and business leadership translating platform capability into business outcomes and ensuring organizational alignment on data standards and prioritization.
  • Build, grow, and retain a high-performing team of data and knowledge engineers, setting a culture of velocity, ownership, and measurable accountability at every layer of the stack.
  • Drive the architecture and expansion of Wolfe's knowledge foundations including systematic onboarding of new data sources so that growth in data complexity creates clarity, not chaos.

Impact Statement: For more clarity on the role, below are the success metrics and measurements for this role in the first 90 to 120 days.
  • Data trust is quantified, not assumed: A data quality scoring system is live across all core data sources, with at least 90% of priority datasets rated and documented and a defined SLA for how quickly a data quality issue is identified, escalated, and resolved (target: under 24 hours from detection to remediation).
  • New source onboarding is systematized and proven: A repeatable ingestion onboarding process is documented and has been successfully used to bring at least one net-new data source from scoping to production in 30 days or fewer, with zero regression to existing pipelines.
  • AI teams are unblocked and self-sufficient: At least two active AI product teams can independently identify which data sources to rely on for their use case measured by a reduction in ad hoc data questions escalated to the platform team by at least 50% compared to baseline at time of hire.

Qualifications
  • 10+ years of progressive experience in data platform, data engineering, or knowledge infrastructure with at least 5 years in a senior leadership role owning a team, a budget, and a multi-year roadmap.
  • Executive-level track record of building or scaling a data platform at a high-growth technology company, ideally in an AI-native or AI-first environment where semantic data structure and reliability are core product requirements.
  • Deep fluency in modern data stack components including vector databases, embedding pipelines, and LLM-adjacent infrastructure with the authority and experience to make high-stakes architectural decisions and hold engineering teams accountable to them.
  • Proven ability to operate at the executive level: aligning C-suite stakeholders, communicating complex platform tradeoffs in business terms, and driving company-wide adoption of data standards through influence rather than mandate.
  • Founder-level ownership mindset you define the outcome, build the team to deliver it, remove the blockers, and measure everything.

Compensation, Benefits, and Perks
The compensation shown includes Base Salary plus Target Incentives Bonus. In addition, you will receive RSUs. Wolfe is committed to providing a comprehensive benefits package to support your well-being, along with competitive compensation. Our benefits and perks include but not limited to:
  • Restricted Stock Units (RSUs)
  • Incentive Bonus
  • Profit Share
  • Medical, Prescription, Vision, and Dental insurance for employees and dependents (Wolfe pays 80% of premium)
  • Short-Term Disability Insurance (Wolfe pays 100% of premium)
  • Voluntary Long-Term Disability Insurance, Life Insurance, Critical Illness Insurance, Accident Insurance, and Hospital Indemnity coverage
  • PTO (vacation and sick time)
  • Corporate Holidays and Floating Holidays
  • 401(k)
  • Employee recognition program
  • Charitable Donation to a charity of your choice yearly
  • Employee Referral Bonus
  • Tuition Reimbursement
  • Internal Training and Information sessions
  • Family Picnic, Holiday Party, and other outings
  • Internal Culture Club

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