Lead Project Data Analytics Management Specialist

Boeing•Saint Charles, MO

21h•Onsite

About The Position

Boeing, Defense, Space, and Security (BDS) is seeking a motivated, talented Lead Project Data Analytics Management Specialist to join the Precision Engagement Systems (PES) team. This role is a 50/50 Program Management + Data Analytics position, focusing on workforce/resource planning and program facilitation, while also building analytics, automated ETL, and leadership dashboards for data-driven engineering decisions. The successful candidate will excel at facilitating engineering processes, driving improvements, and delivering actionable insights through data analysis and automation. A strong passion for people's development and engagement is essential. This role serves as a key process facilitator and data analytics expert supporting engineering workforce staffing, resource planning, and other critical engineering functions within the Space, Intelligence and Weapon Systems (SIWS) organization. Collaboration with functional engineering partners, engineering leaders, and teams from Government Operations, Legal, Human Resources, and Finance is expected to ensure alignment with Boeing’s Engineering mission.

Requirements

Ability to obtain a U.S. Security Clearance for which the U.S. Government requires U.S. Citizenship. An interim and/or final U.S. Secret clearance Post-Start is required.
5+ years of experience of working independently and collaboratively in a team environment
3+ years building data analytics dashboards and business intelligence solutions in Power BI or Tableau; demonstrable work with Power Query and DAX
Hands-on experience with at least one scripting language for data automation (Python, R, or equivalent)
Proven experience facilitating workforce staffing or other resource planning processes within technical or engineering organizations
Strong data analysis and automation skills, with demonstrated ability to collect, interpret, and streamline complex data sets
Proven ability to design KPIs, run trend/variance analyses, forecasting, and present actionable insights to senior leadership.
Excellent verbal and written communication skills, with the ability to collaborate effectively with engineers, engineering leadership, and cross-functional teams

Nice To Haves

3+ years of program or project management experience supporting engineering, product development, or technology programs
Bachelor's degree or higher
Experience with data pipeline/ETL tooling, cloud data platforms, or orchestration (Azure Data Factory, Airflow, etc.)
Experience with Tableau, Looker, or other advanced visualization platforms in addition to Power BI
Experience writing SQL for data transformation, reporting, and analytics
Familiarity with data modeling best practices, dimensional modeling, and build/ maintain enterprise datasets
Experience with large-scale workforce planning, skills-based staffing, or labor forecasting
Formal project management training/certification (PMP, CAPM, ScrumMaster) is a plus
Experience in financial analysis, budgeting, or cost modeling to support resource allocation decisions
Prior experience supporting cleared programs or government customers

Responsibilities

Develop and operationalize analytics, automated ETL pipelines, and dashboards to support workforce planning and engineering program decisions
Design, compute, and maintain KPIs, trend/variance analyses, forecasting, and risk models; translate findings into actionable staffing and program recommendations
Build and maintain data models in Power BI (Power Query), author DAX measures, write SQL queries, and use scripting (Python/R) to automate data workflows and validation
Create executive-ready reports, visualizations, and briefings; present insights and recommended actions to senior leadership
Facilitate recurring resource planning cycles, cross-functional governance, technical reviews, and large-scale events to align stakeholders and drive program outcomes
Drive process improvement and change management initiatives that implement analytics-driven decisions and reduce manual effort
Establish and enforce data quality standards, definitions, and documentation for workforce and program datasets
Partner with HR, Finance, Legal, Government Operations, and engineering leadership to ensure analytics address operational needs and compliance
Lead adoption of analytics platforms and coach stakeholders on metrics interpretation and data-driven decision making
Document lessons learned and support program closeout and transition activities.