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Vice President Data Engineering Jobs in Missouri

PROENERGY

Vice President PowerFLX

Sedalia, MO · On-site

Vice President PowerFLX About PROENERGY PROENERGY is an engineering, R amp;D, and manufacturing ... Report division performance to SVP and CEO, providing data-driven insights on progress and risk ...

SupportFinity™

VP of Engineering

California, MO · On-site

$260 - $380/hr

We are seeking a deeply technical VP of Engineering who can navigate the challenges of rapid growth ... data. At Medplum, we have a unique opportunity to impact the lives of patients, speed medical ...

New

MasterCard

Vice President Platform Engineering

O Fallon, MO · On-site

$168K - $217K/yr

Title and Summary Vice President Platform Engineering Overview MSBX (Mastercard Secure Build Experience) is driving the next generation of the software engineering experience for more than 11,000 ...

Brightli

Vice President Finance - Remote

Springfield, MO · Remote

... data-informed decision-making across all markets and service lines. The VP of Finance will play a ... critical role in aligning financial strategies with Centerstone's mission, vision, and long-term ...

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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 Missouri?

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

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

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

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

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

What cities in Missouri are hiring for Vice President Data Engineering jobs?

Cities in Missouri 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 Missouri as of June 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 76% In-person, 4% Hybrid, and 20% Remote job distribution.

VP of Data Analytics & AI

NCM Associates

Kansas City, MO • On-site

Full-time

Re-posted 5 days ago

Job description

The Vice President of Data, Analytics & AI will lead our new Data, Analytics, and AI function, reporting directly to the COO. The VP, Data is responsible for defining and executing the enterprise data, analytics, and AI roadmap to enable connected and flexible data, client-facing digital products, and capabilities ranging from data governance and data management to architecture and engineering. This role provides executive leadership for data, analytics, and AI within the Data function and across NCM, ensuring data assets are scalable, secure, and aligned to business strategy. The VP will build and lead high-performing teams, modernize data platforms, govern data and AI responsibly, and deliver assets and digital products that generate measurable value for our business and our clients.

Duties and Responsibilities

Executive Leadership

  • Define and execute the enterprise data, analytics, and AI roadmap and investment plans aligned to business strategy.
  • Assess organizational readiness for data initiatives, including processes, tools, skills, and culture.
  • Forecast data, infrastructure, and resource needs to support business demand and transformation initiatives.
  • Partner with executive leaders to prioritize initiatives and ensure stakeholder alignment.

Data Governance, Risk & Compliance

  • Develop, implement, and enforce enterprise data policies to ensure regulatory compliance, ethical use of data, and risk mitigation.
  • Ensure ownership, management, and stewardship of data assets across the data lifecycle.

Digital Products & Value Delivery

  • Own the lifecycle management of data, analytics, and AI products, from ideation and prioritization through delivery and ongoing enhancement to create and maintain high-quality, reusable data assets
  • Define and link key performance indicators (KPIs) to digital products to measure business impact and drive continuous improvement.
  • Plan the evolution of digital products with clear timelines, dependencies, and milestones to ensure reliability, performance, and user satisfaction.
  • Foster a culture of data-driven decision-making across the organization through enablement and self-service analytics.

Artificial Intelligence & Machine Learning

  • Lead the introduction of AI and machine learning solutions to automate processes and enhance business outcomes.
  • Ensure responsible AI practices, including bias mitigation, explainability, and compliance with internal and external standards.

Data Architecture & Engineering

  • Guide architecture and engineering to create and maintain standardized, connected, and flexible data structures across the enterprise.
  • Standardize key data domains (e.g., customer, product, reference data), data integration patterns, and data storage solutions to ensure high-quality data, reusable data assets, seamless interoperability with internal and external systems, scalability, performance and cost optimization.

Data Operations, DevOps & Platform Modernization

  • Enable collaborative, automated, and reliable data operations.
  • Implement processes and technologies to accelerate delivery and reduce risk.
  • Implement encryption, access management, and security controls for data at rest and in motion to ensure data privacy and compliance.
  • Ensure applications are scalable, performant, and integrated with enterprise data platforms.

Talent Development & Enablement

  • Build, lead, and mentor multidisciplinary teams across data governance, data management and stewardship, architecture, data engineering, analytics, AI, and platform operations.
  • Deliver training and enablement programs to build data literacy and advanced skills across the organization.
  • Establish career paths, performance standards, and a culture of innovation and continuous improvement.

Qualifications

  • 15+ years of experience in data, analytics, and technology leadership, with significant experience at the enterprise level.
  • Proven track record of delivering large-scale data, analytics, and AI initiatives that drive measurable business outcomes.
  • Deep expertise in data governance, analytics, architecture (business, data, integration, and solution architecture), and modern data platforms.
  • Strong understanding of regulatory, privacy, and ethical considerations related to data and AI.
  • Demonstrated ability to influence executive stakeholders and translate business strategy into technical execution.
  • Experience building and leading high-performing, cross-functional teams and leading those teams through change and ambiguity