Senior Data Engineer

Space Force Service Wide Support Activities•Universal City, TX

About The Position

The United States Space Force at Randolph AFB in San Antonio, Texas, is hiring a Senior Data Engineer for the Enterprise Talent Management Office (ETM). The role builds and sustains data capabilities that inform Guardian talent management and senior-leader decisions. It develops and improves data models, pipelines, interfaces, and infrastructure; integrates diverse data sources; and delivers timely, reliable analytics for human capital policy, workforce planning, and talent operations. The position applies advanced data engineering, statistical analysis, artificial intelligence, machine learning, simulation, and decision-analysis methods to complex enterprise challenges. As a technical subject matter expert, the employee translates stakeholder needs into technical requirements and turns complex data into actionable recommendations for Space Force decision-makers. The role leads data engineering and analytics initiatives, strengthens data quality, governance, and reliability, and prepares concise reports and briefings for senior, nontechnical audiences. This is a NH-1560-04 position, equivalent to GS-14/15. The position is eligible for situational telework only, including emergency and OPM-prescribed unscheduled telework. Travel by military or commercial aircraft may be required for temporary duty, approximately 63 days per year. PCS/relocation may be authorized; incentives are not authorized.

Requirements

U.S. citizenship.
Ability to obtain and maintain a Secret security clearance.
Must handle and safeguard sensitive and/or classified information in accordance with regulations.
Bachelor's degree in mathematics, statistics, computer science, data science, or another field directly related to the position, or a qualifying combination of education and experience under the applicable qualification standard.
At least 24 semester hours in a combination of operations research, mathematics, probability, statistics, mathematical logic, science, or subject-matter courses requiring substantial competence in college-level mathematics or statistics; at least 3 of the 24 semester hours must be in calculus.
Experience developing and maintaining data pipelines, data models, databases, and data infrastructure.
Experience using SQL and scripting or statistical-computing languages such as Python or R for data processing and analysis.
Experience designing, training, validating, and evaluating AI or machine-learning models.
Experience performing statistical analysis, predictive modeling, simulation, optimization, or decision analysis.
Experience establishing data governance, metadata, data-quality, testing, and monitoring practices.
Experience leading technical projects or teams, managing competing priorities, and delivering results on schedule.
Experience explaining complex technical findings through concise reports and briefings for senior, nontechnical audiences.
Knowledge of computer science, data analytics, statistics, mathematics, data modeling, database design, data storage, data governance, metadata management, and regulatory considerations for data use.
Ability to design and deliver scalable data pipelines and data models using reproducible and repeatable engineering processes.
Programming skills and proficiency in data query languages and scripting for data processing.
Skill in programming, training, and validating AI and ML models to synthesize disparate and messy data for mission requirements.
Skill in implementing data quality, testing, and monitoring practices for data production systems.
May be required to travel by military or commercial aircraft on temporary duty, approximately 63 days per year.

Responsibilities

Develop and maintain data pipelines, models, databases, and data infrastructure.
Integrate diverse data sources and deliver reliable analytics for human capital policy, workforce planning, and talent operations.
Design, train, validate, and evaluate artificial intelligence and machine-learning models.
Apply statistical analysis, predictive modeling, simulation, optimization, and decision-analysis methods to complex organizational and mission challenges.
Lead data engineering and analytics initiatives, technical projects, or teams and manage competing priorities.
Translate stakeholder needs into technical requirements and deliver scalable data pipelines, models, dashboards, and interfaces.
Establish and strengthen data governance, metadata, data-quality, testing, and monitoring practices.
Explain complex technical findings through concise reports and briefings for senior, nontechnical audiences.
Turn complex data into clear, actionable recommendations for Space Force decision-makers.