Data Product Manager

Job Title: Data Product Manager

Location: Arnold AFB, TN

Job Family Code: Q – Program Management & Operations (tech)

Function/Branch: MIS/Data Team

Directorate: MIS

Position Type:  Regular, Full-Time

Pay Type: Exempt

Sponsorship: Position Not Sponsored

Grade: L10 (QA1005)/L11 (QA1103)

Salary Range or Starting Hourly Rate: L10: $146,500 - $179,000; L11: $160,000 - $213,000/ per year

Overview

BNH is seeking a strategic, business-oriented Data Product Manager to lead our enterprise data transformation and define the roadmap for BNH’s data products supporting the TOS II contract at Arnold Air Force Base. In this hands-on leadership role, you will treat enterprise data as a core product, bridging the gap between technical teams (data engineering, analytics, business intelligence) and key business stakeholders (aerospace test operations, finance, and compliance). You will define product vision, manage the data product backlog, and lead the technical team in delivering secure, self-service data capabilities that support aerospace testing throughput.

As a key member of the senior leadership team, the Data Product 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

Open to internal & external candidates. The selected candidate for this requisition may be required to occasionally (e.g. application upgrades) work outside normal business hours.

Job Summary

The successful candidate will be a strategic, business-oriented data leader responsible for defining the enterprise data product vision, establishing the long-term product roadmap, managing and prioritizing the feature backlog, and optimizing resource investments to ensure BNH’s data assets deliver measurable business value and directly support the modernization goals of the TOS II contract.

Job Duties and Key Responsibilities:

• Strategic leadership: 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.
• Team Leadership: 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
• Cross-Functional Team Coordination: 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.
• Product Roadmap & Delivery: Define product-level Objectives and Key Results (OKRs) and establish product success criteria; manage the data product lifecycle from concept through launch, user adoption, and continuous iteration. Maximize team velocity and resource allocation using Agile product management tools, shifting focus from "delivering on time" to "delivering high-value, high-adoption features.
• Requirement Translation: Convert high-level business goals into clear, actionable technical requirements for the data team.
• Test Operations Modernization: Partner with O&M, instrumentation, and test engineering directorates to design and modernize legacy data acquisition and telemetry pipelines. Build secure, reliable data products that scale testing capacity, directly supporting the contract's goal to double testing throughput.
• Data Governance and Quality Management: 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.
• Data Product Lifecycle Management: Define the long-term vision, strategy, and product roadmap for BNH’s data infrastructure, analytics dashboards, and automated reporting systems.
• Workflow Management: Utilize Agile frameworks like Scrum or Kanban to manage data pipelines, handle unknowns, and iterate deliverables.
• Stakeholder Communication and Reporting: Translate complex technical progress into plain-language business insights for non-technical stakeholders and keep leadership informed on project health, risks, and ROI.
• Perform other duties as required.

Basic Qualifications:

• Bachelor's in computer science, data science, software engineering, information systems, business analytics, or operations reasearch, OR Bachelor's degree in any field, plus 2 additional years of expereince in technical data management or product analytics.

• (10) Ten Years as a product owner, product manager, data scientist, business intelligence, data engineering or data analytics.
• Must be able to obtain and maintain an active security clearance and mainatain authorized user access to the AEDC local area network.
• U.S. Citizenship is required due to federal governement contract compliance requirements and the necessity to access secure federal databases and networks on Arnold Air Force Bsae.

Preferred Qualifications

• Data Management Fundamentals: Understanding of data warehousing, ETL (Extract, Transform, Load) pipelines, database structures, and data modeling.
• Enterprise-Scale Modernization: Experience migrating legacy on-premises systems (e.g., legacy databases, analog test telemetry) to modern, cloud-based data warehouses or unified lakes.
• Business Intelligence & Analytics Tools: Familiarity with visualization and reporting platforms like Tableau, Power BI, or Looker.
• Data Science & Big Data Concepts: Working knowledge of how machine learning models, big data frameworks, and analytics workflows operate.
• Query & Scripting Basics: Literacy in foundational languages or tools like SQL or Python to communicate effectively with technical contributors
• Translation & Communication: Ability to explain complex technical metrics and machine learning outputs in plain language to non-technical business partners.
• Collaboration Frameworks: Experience running agile or hybrid project frameworks (such as Scrum or Kanban).
• Problem-Solving & Critical Thinking: Aptitude for troubleshooting data bottlenecks, missing variables, or shifting project requirements.
• Stakeholder Management: Skill in balancing competing demands, managing expectations, and driving project buy-in across different departments.

What We Offer

• Competitive salaries
• Continuing education assistance
• Multiple healthcare benefits packages
• 401K with employer matching
• Paid time off (PTO) along with a federally recognized holiday schedule