Vp Of Data Engineering information
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$112.5K - $138.5K
1% of jobs
$138.5K - $164.5K
7% of jobs
$177.7K is the 25th percentile. Wages below this are outliers.
$164.5K - $190.5K
33% of jobs
The median wage is $198.4K / yr.
$190.5K - $216.5K
29% of jobs
$224.4K is the 75th percentile. Wages above this are outliers.
$216.5K - $242.5K
15% of jobs
$242.5K - $268.5K
5% of jobs
$268.5K - $294.5K
5% of jobs
$294.5K - $320.5K
3% of jobs
$320.5K - $346.5K
1% of jobs
$346.5K - $372.5K
0% of jobs
$372.5K - $398.5K
0% of jobs
How much do vp of data engineering jobs pay per year?
As of Sep 11, 2026, the average yearly pay for vp of 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.
A VP of Data Engineering is a senior executive responsible for leading and overseeing the data engineering team within an organization. Their primary duties include setting the vision and strategy for data infrastructure, ensuring data quality and security, and enabling data-driven decision-making across the company. They collaborate with other leaders to align data initiatives with business goals, manage large-scale data projects, and mentor engineering teams. Additionally, they stay current with emerging technologies to keep the organization's data capabilities competitive.
To thrive as a VP of Data Engineering, you need deep expertise in data architecture, engineering best practices, and team leadership, typically backed by a degree in computer science and extensive industry experience. Familiarity with big data platforms (like Hadoop and Spark), cloud services (AWS, Azure, GCP), and data pipeline orchestration tools is essential, and certifications in cloud or data engineering are highly valued. Outstanding communication, strategic vision, and the ability to mentor and inspire teams set top performers apart. These skills enable effective scaling of data infrastructure, alignment with business goals, and fostering high-performing, innovative engineering teams.
A VP of Data Engineering often encounters challenges such as scaling data infrastructure to meet business needs, ensuring data quality and consistency, and aligning data initiatives with organizational goals. Addressing these challenges typically involves fostering close collaboration between engineering, analytics, and business teams, as well as implementing robust data governance frameworks. Proactive communication, setting clear priorities, and investing in team development are also essential for overcoming obstacles and driving data strategy effectively.
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What states have the most Vp Of Data Engineering jobs?
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