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# Data Engineer, Mid

- **Company:** Booz Allen Hamilton Inc.
- **Location:** McLean, VA, United States
- **Experience:** Experienced
- **Salary:** $62,000.0 - $141,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Amazon S3, Build Automation, Big Data, Cloud Computing, Code Review, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Relational Databases, Database Development, Database Queries, Github, Python (Programming Language), Metadata, Performance Tuning, Query Optimization, DataOps, Software Configuration Management, SQL Databases, Automated Data Processing (ADP), Data Processing, Cloud Platform System, Data Classification, GitHub Copilot, Delivery Pipeline, Apache Spark, Git, Data Lakes, Pyspark, Data Lineage, Physical Data Models, GPT, Data Pipelines, Devsecops, Jenkins, Databricks
- **Published:** October 31, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88757268/1

## About the Role

* 3+ years of experience in data engineering, database development, or data warehousing
 * Experience developing data pipelines using Python, and Apache Spark or PySpark for processing large datasets
 * Experience with Git or GitHub for source-code management and collaborative development
 * Experience with Jenkins, SQL, including complex queries, joins and aggregations, CTEs, window functions, query optimization, and performance tuning, and relational databases, including database development, troubleshooting, and performance considerations
 * Knowledge of data warehousing concepts, including ETL/ELT, fact and dimension tables, star and snowflake schemas, slowly changing dimensions, and data integration, and data quality concepts, including data validation, completeness, accuracy, consistency, duplicate detection, and data reconciliation
 * Knowledge of data modeling, including conceptual, logical, and physical data models, and data governance, including data ownership and stewardship, metadata, data lineage, data security, data classification, and data standards
 * Knowledge of CI/CD pipelines, including automated builds, testing, and deployments
 * Ability to develop and support Spark-based processing workflows
 * Public Trust
 * Bachelor's degree

Nice If You Have:

 * Experience with Databricks or similar cloud-based data platforms
 * Experience with Amazon Web Services (AWS)
 * Experience with AWS services such as S3, Glue, Lambda, or similar technologies
 * Experience with data lake or Lakehouse environments
 * Experience with DevSecOps practices, Infrastructure-as-Code, or automated data quality checks
 * Experience working with large or complex datasets
 * Experience working in federal or other highly regulated environments
 * Ability to effectively use approved AI-assisted development tools such as GitHub Copilot, ChatGPT, Amazon Q, or similar tools, to improve productivity, troubleshoot issues, generate and review code, create documentation, and accelerate learning while following organizational security and data-protection standards

Vetting:

Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client; Public Trust determination is required.

## Description

As a data engineer on our team, you'll work with experienced engineers and technical teams to design, develop, test, and maintain data pipelines and data processing workflows. You'll use modern data engineering technologies such as Databricks and Python to integrate, transform, and move data across enterprise environments.

This is an opportunity to grow your data engineering expertise while working with cloud technologies, automation, and modern data platforms. You'll collaborate with developers, data engineers, and stakeholders to solve technical challenges and deliver scalable solutions. Due to the nature of work performed within this facility, U.S. citizenship is required.

What You'll Work On:

 * Develop and maintain data pipelines and automated data processing workflows.
 * Build data transformations and processing workflows using Databricks, SQL, and Python.
 * Integrate data from multiple sources and formats.
 * Automate repetitive data processing and operational tasks.
 * Test, troubleshoot, and optimize data pipelines for reliability and performance.
 * Collaborate with senior engineers and technical teams to implement data solutions.
 * Participate in Agile development, code reviews, testing, and deployment activities.
 * Contribute to technical documentation and data engineering best practices.