Business Intelligence Engineer

Booz Allen Hamilton•McLean, VA

1d•$77,600 - $176,000

About The Position

Booz Allen is seeking a data-driven Business Intelligence Engineer to turn large enterprise datasets into actionable insights. This internal-facing analyst will work primarily with pipeline, relationship management, and financial systems, combining data engineering, modeling, and analytical expertise with strong communication skills to help company leadership identify trends and measure performance. U.S. citizenship is required because of the nature of the work performed within the facility. The role supports the company’s opportunity pipeline and CRM system, develops dashboards and reports, builds and maintains scalable data models and datasets, and applies statistical methods and AI tools to improve business intelligence and automation. The position also involves optimizing cloud storage and data pipeline performance using knowledge of data lake or warehouse architecture. The projected annualized compensation range is $77,600 to $176,000. Booz Allen describes benefits that include health, life, disability, financial, and retirement benefits; paid leave; professional development; tuition assistance; work-life programs; dependent care; and recognition awards. Eligibility for benefit programs depends on employment status and hours worked.

Requirements

At least 5 years of experience in data modeling, analytics, or business intelligence.
At least 3 years of experience with Power BI and Tableau dashboards.
Knowledge of relational databases and dimensional modeling.
Knowledge of data engineering syntax and its application.
Bachelor’s degree.
U.S. citizenship is required.

Nice To Haves

Experience with Salesforce.
Ability to communicate complex data concepts simply to senior leadership.
Excellent communication and presentation skills.

Responsibilities

Serve as a business intelligence engineer and data analyst for the company’s opportunity pipeline and CRM system.
Gather insights and trends about opportunities, contacts, and lead generation to support bid and resourcing decisions.
Create dashboards and reports using Power BI and Tableau.
Apply statistical concepts, including regression models, probability distributions, and Monte Carlo simulations.
Design and maintain scalable data models for reporting, dashboards, and advanced analytical needs.
Build and optimize datasets in Databricks using SQL, Spark, Python, or other applicable syntax and tools.
Use Agentforce and other applicable AI tools to develop automated solutions.
Apply data lake or warehouse architecture expertise to optimize cloud storage and pipeline performance.
Automate manual processes to simplify analysis and interpretation of KPIs and trends.
Communicate findings and discuss trends and performance with company leadership.