Data Engineer

Booz Allen Hamilton•McLean, VA

1d•Remote

About The Position

Data is only as powerful as the pipelines that move it, the structure that organizes it, and the trust that supports it. As a Data Engineer, you’ll help build and scale a cloud-native data platform that enables mission-critical insights across the enterprise. In this role, you’ll design, build, and optimize data pipelines that ingest, transform, and deliver data from a wide range of internal and external sources. You’ll work within a modern AWS-based data ecosystem to support analytics, APIs, and AI/ML use cases ensuring data is reliable, secure, and accessible to those who need it. You’ll collaborate closely with cloud engineers, API developers, data analysts, and mission stakeholders to develop reusable data products and scalable ingestion frameworks. From batch ingestion to near real-time processing, your work will directly support national security missions by turning raw data into actionable intelligence. Work with us to build the backbone of enterprise data. Join us. The world can’t wait.

Requirements

3+ years of experience in data engineering, data integration, or backend data development
Experience designing, building, and maintaining ETL/ELT data pipelines
Experience in SQL and Python
Experience ingesting and integrating data from multiple sources such as APIs, flat files, and databases
Experience with cloud-based data platforms, including AWS, and distributed data processing
Experience working in Agile development environments and collaborating with cross-functional teams
Ability to translate technical data concepts for stakeholders
Top Secret clearance
Bachelor's degree in Computer Science, Data Science, or Engineering

Nice To Haves

Experience with AWS services such as Amazon S3, AWS Glue, Amazon Athena, AWS Lambda, or Amazon Redshift
Experience implementing data validation, quality checks, and monitoring within pipelines
Experience with data lake or lakehouse architectures and columnar storage formats such as Parquet
Experience with big data frameworks such as Apache Spark and supporting data platforms, analytics environments, or AI/ML pipelines
Experience with DevSecOps practices and tools, including GitLab CI/CD or Terraform
Knowledge of data modeling concepts and data pipeline architectures such as medallion or layered approach
Knowledge of API-driven data access and event-driven integration patterns
Ability to optimize data workflows for performance, scalability, and reliability
Possession of strong problem-solving skills
IAT Level II, CompTIA Security+, Computing Environment, or AWS CCP Certification

Responsibilities

Design, build, and optimize data pipelines that ingest, transform, and deliver data from a wide range of internal and external sources.
Work within a modern AWS-based data ecosystem to support analytics, APIs, and AI/ML use cases ensuring data is reliable, secure, and accessible to those who need it.
Collaborate closely with cloud engineers, API developers, data analysts, and mission stakeholders to develop reusable data products and scalable ingestion frameworks.