Project Manager - Data with Security Clearance

Data Project Manager – Active DoD Secret Clearance Required Job Location: Arnold AFB, Tullahoma, TN 37388 (On Site) Clearance: Current and Active DoD Secret Clearance Relocation: Candidates willing to relocate within 2-4 weeks from offer will be considered.

Compensation: dependent on a combination of education, skills, and years of experience. Send resumes to: in addition to applying online. Job Summary
Our client is seeking a Data Project Manager at Arnold Air Force Base in Arnold, TN. We are seeking a strategic, business-oriented Data Project Manager to lead our enterprise data capabilities and maximize the business value derived from data across the organization. The Data Project Manager will lead our enterprise data capabilities and maximize the business value derived from data across the organization.

This role will guide data-centric initiatives—such as data migrations, business intelligence rollouts, and analytics model deployments—from start to finish, acting as a critical bridge between technical teams and business stakeholders. As a key member of the senior leadership team, the Data Project Manager will define and execute the organization’s data strategy, ensuring that data becomes a core driver of business performance, innovation, and competitive advantage. This is a hands-on leadership role that balances strategic vision with operational excellence
Job Duties

• Define and continuously evolve the enterprise data strategy aligned with business objectives; Establish KPIs that directly link data initiatives to business outcomes (revenue growth, churn reduction, cost savings, etc.); Act as the primary advocate for data initiatives at the executive level.
• Build, lead, and scale a high-performing Data team (Data Engineering, Analytics, Data Science, Governance); Foster a culture of innovation, continuous learning, and technical excellence; Set priorities and make final decisions on project resourcing.
• Lead and act as a bridge between cross-functional teams of data engineers, data scientists, analysts, and business leaders to ensure alignment and unblock technical progress.
• Define project scope, objectives, and success criteria; create detailed timelines, manage resources, and oversee budgets to deliver work on time and within financial limits.
• Convert high-level business goals into clear, actionable technical requirements for the data team.
• Oversee enterprise data governance, data quality, master data management, and data security; Ensure data collection, storage, and sharing comply with internal data governance standards, security policies and compliance with all regulatory and privacy requirements; Anticipate and mitigate technical, ethical, or financial hurdles while ensuring data accuracy; Champion best practices in data architecture and data management.
• Utilize Agile frameworks like Scrum or Kanban to manage data pipelines, handle unknowns, and iterate on project deliverables.
• Translate complex technical progress into plain-language business insights for non-technical stakeholders and keep leadership informed on project health, risks, and ROI.

Basic Qualifications

• 6+ years of experience in data, analytics, or data science roles
• B.S. degree in a relevant field (Data Science, Computer Science, Computer Engineering, Engineering, or IT, or equivalent)
• Proven track record of delivering measurable business value through data initiatives, with at least 5 years in a senior project leadership position • Must be able to obtain and maintain security clearance and the AEDC local area network.
• Current and active Secret security clearance required
• Automation experience may be substituted with other relevant IT experiences.

• Understanding of data warehousing, ETL (Extract, Transform, Load) pipelines, database structures, and data modeling.
• Familiarity with visualization and reporting platforms like Tableau, Power BI, or Looker.
• Working knowledge of how machine learning models, big data frameworks, and analytics workflows operate.
• Literacy in foundational languages or tools like SQL or Python to communicate effectively with technical contributors.
• Ability to explain complex technical metrics and machine learning outputs in plain language to non-technical business partners.
• Experience running agile or hybrid project frameworks (such as Scrum or Kanban).
• Aptitude for troubleshooting data bottlenecks, missing variables, or shifting project requirements.
• Skill in balancing competing demands, managing expectations, and driving project buy-in across different departments.