Data Project Manager

Archarithms Inc•Tullahoma, TN

10d

About The Position

Arcarithm is seeking a strategic, business-oriented Data Project Manager at Arnold Air Force Base in Arnold, Tennessee. The role leads enterprise data capabilities and initiatives—including data migrations, business intelligence rollouts, and analytics model deployments—to maximize the business value derived from data. It serves as a bridge between technical teams and business stakeholders and balances strategic vision with operational execution. As a member of the senior leadership team, the Data Project Manager defines and executes the organization’s data strategy, positioning data as a driver of business performance, innovation, and competitive advantage. The role also leads and scales a multidisciplinary Data team and oversees project delivery, governance, quality, security, and compliance.

Requirements

At least 6 years of experience in data, analytics, or data science roles.
Bachelor of Science degree in a relevant field, such as Data Science, Computer Science, Computer Engineering, Engineering, or IT, or equivalent.
Proven track record of delivering measurable business value through data initiatives, including at least 5 years in a senior project leadership position.
Must be able to obtain and maintain a security clearance and access to the AEDC local area network.
Current U.S. citizenship is required.
Automation experience may be substituted with other relevant IT experience.

Nice To Haves

Understanding of data warehousing, ETL pipelines, database structures, and data modeling.
Familiarity with visualization and reporting platforms such as Tableau, Power BI, or Looker.
Working knowledge of machine learning models, big data frameworks, and analytics workflows.
Literacy in foundational languages or tools such as 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 departments.

Responsibilities

Define and continually evolve the enterprise data strategy in alignment with business objectives, establish KPIs linked to business outcomes, and advocate for data initiatives at the executive level.
Build, lead, and scale a high-performing Data team across data engineering, analytics, data science, and governance; foster innovation, continuous learning, and technical excellence; set priorities and make final project-resourcing decisions.
Bridge 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; develop timelines, manage resources, oversee budgets, and deliver work on time and within financial limits.
Translate 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 practices comply with internal standards, security policies, regulatory requirements, and privacy requirements.
Anticipate and mitigate technical, ethical, or financial hurdles while ensuring data accuracy, and champion data architecture and data management best practices.
Use Agile frameworks such as Scrum or Kanban to manage data pipelines, address unknowns, and iterate on deliverables.
Translate technical progress into plain-language business insights and keep leadership informed about project health, risks, and ROI.