Data Engineer, Senior

Booz Allen Hamilton is seeking a Senior Data Engineer in McLean, VA to design, develop, and maintain scalable, cloud-based data pipelines and automated data workflows. This role supports mission-critical applications and analytics, with a focus on reliability, performance, and repeatable delivery. U.S. citizenship and a Public Trust determination are required.

What You’ll Do

• Design, develop, test, and maintain scalable data pipelines and data processing workflows.
• Build and maintain data solutions using Databricks, including data transformation, processing, and orchestration.
• Create automated workflows that improve reliability, efficiency, and repeatability of data processing.
• Integrate data from multiple sources and formats into enterprise data platforms.
• Develop and optimize data transformations using SQL and Python.
• Troubleshoot pipeline issues and identify opportunities to improve performance and reliability.
• Collaborate with software developers, data engineers, architects, and stakeholders to understand requirements and deliver technical solutions.
• Apply Agile practices, version control, testing, and CI/CD across the software development lifecycle.

Required Qualifications

• 5+ years of experience in data engineering, database development, or data warehousing.
• Strong SQL experience, including complex queries, joins and aggregations, CTEs, window functions, query optimization, and performance tuning, along with relational database development, troubleshooting, and tuning.
• Experience developing and maintaining data pipelines using Python, including Apache Spark or PySpark for processing and transforming large datasets, with performance optimization and troubleshooting.
• Experience with Databricks.
• Experience with AWS and AWS data services including S3, EMR, Glue, Lambda, or NoSQL databases.
• Experience with CI/CD pipelines, including GitHub Actions, for automated builds, testing, deployment, and promotion across environments.
• Knowledge of database design principles and data warehousing concepts, including ETL/ELT, fact and dimension tables, star and snowflake schemas, slowly changing dimensions, data integration, and incremental data processing.
• Ability to independently troubleshoot data pipeline failures, data issues, performance problems, and production incidents, identify root causes, and determine corrective actions.
• Public Trust.
• Bachelor’s degree in CS.

Technologies

• Databricks
• AWS (S3, EMR, Glue, Lambda)
• SQL
• Python
• Apache Spark, PySpark
• GitHub Actions
• NoSQL databases

Additional “Nice If You Have”

• Experience with data lake or Lakehouse architectures.
• Experience with DevSecOps practices.
• Experience working in federal or other highly regulated environments.
• Knowledge of data modeling, including conceptual, logical, and physical models, dimensional modeling, and designing models that support analytics and reporting requirements.
• Ability to contribute to technical design and architecture discussions and evaluate implementation approaches to build scalable, maintainable, and reliable data engineering solutions.
• Ability to use AI-assisted development tools for development productivity, code generation and review, troubleshooting, SQL and Spark optimization, documentation, and accelerated learning while following organizational security and data-protection standards.

Benefits

• Health, life, disability, financial, and retirement benefits
• Paid leave
• Professional development
• Tuition assistance
• Work-life programs
• Dependent care
• Recognition awards program

Vetting and Identity Verification

• Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client; a Public Trust determination is required.
• During the hiring process, you will complete an identity verification process that leverages advanced biometrics and artificial intelligence. You are expected to be on camera during interviews and assessments, and the company reserves the right to take your picture to verify your identity and prevent fraud.
• AI usage policy: use of artificial intelligence (AI) or other tools to assist with responses during interviews (in-person or virtual) is prohibited unless permission is explicitly provided.

Compensation and Work Model

Projected compensation range: USD 77,600 to 176,000 per year (annualized USD).

Work model: Onsite in McLean, VA, primarily full-time at a customer facility, with collaboration alongside colleagues and customers as required by the role. Employees working virtually are generally expected to have their cameras on during meetings.