Data Engineer, Senior

Data Engineer, Senior

The Opportunity:  

As a data engineer, you’re excited at the prospect of unlocking the secrets held by a data set, and you’re fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data engineer at Booz Allen, you can help turn these complex data sets into useful information to solve global challenges. Across private and public sectors—from fraud detection to cancer research to national intelligence—we need you to help find the answers in the data. 

On our team, you’ll use your leadership skills and data science expertise to create real-world impact. You’ll work closely with clients to understand their questions and needs, and then dig into their data-rich environments to find the pieces of their information puzzle. You’ll guide teammates and lead the development of algorithms and systems. You’ll use the right combination of tools and frameworks to turn sets of disparate data points into objective answers to advise your clients as they make informed decisions. Ultimately, you’ll provide a deep understanding of the data, what it all means, and how it can be used.

Work with us as we use data science for good.

Join us. The world can’t wait.

You Have:   

• 8+ years of experience correlating complex technical findings into graphical, written, visual, and verbal narrative products

• 5+ years of experience building advanced analytics and AI/ML models, including tools leveraging LLMs or agentic AI, including data retrieval and cleaning, modeling, accuracy evaluation or testing, and visualization

• Experience working on classified networks in support of DoW or IC clients

• Ability to visualize complex data and concepts for non-technical leadership, highlighting system risks and articulating "go or no-go" criteria clearly

• Active TS/SCI clearance; willingness to take a polygraph exam

• Bachelor’s degree and 8+ years of experience with scientific techniques such as mathematics, statistics, information science, AI, machine learning, probability modeling, data mining, data engineering, or data warehousing, or 12+ years of experience with scientific techniques such as mathematics, statistics, information science, AI, machine learning, probability modeling, data mining, data engineering, or data warehousing in lieu of a degree

Nice If You Have:   

• Experience in the development of algorithms leveraging R, Python, or SQL and NoSQL 

• Experience with Distributed data and computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL  

• Experience with visualization packages, including Plotly, Seaborn, or ggplot2 

• TS/SCI clearance with a polygraph  

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation ra