Data Engineer

Booz Allen Hamilton•McLean, VA

6d•$62,000 - $141,000•Remote

About The Position

Data creates pivotal insights when it is collected from disparate sources and organized effectively. As a Mid-Level Data Engineer, you will design, build, and optimize the pipelines that turn raw data into meaningful outcomes for a high-impact Fortune 500 client program. In this role, you will leverage Databricks, PySpark, and SQL to scale our data platforms. You will collaborate within a robust, 70+ person cross-functional ecosystem spanning Data Engineering, AI/Data Science, Governance, and Reporting. As our data strategy evolves, you will also play a key role in integrating new AI technologies and expanding our DataOps and MLOps capabilities. Due to the nature of work performed within this facility, U.S. citizenship is required.

Requirements

3+ years of experience building scalable ETL and ELT workflows for analytics and reporting
3+ years of experience with Python and SQL
3+ years of experience with big data technologies, including Databricks and distributed processing frameworks such as Spark
2+ years of experience with cloud data technologies and architecture
Experience utilizing Spark Structured Streaming to develop real-time low-latency streaming pipelines
Experience delivering solutions in a collaborative, cross-functional team environment
Bachelor’s degree
U.S. citizenship is required

Nice To Haves

Experience with Databricks
2+ years of experience utilizing programming languages, including C++ or Java
2+ years of experience with programming languages such as C, Java, or Python
2+ years of experience working in an Agile development environment
Experience with AI integration, ML workflows, or expanding MLOps capabilities
Knowledge of key components including Unity Catalog, workflows, notebooks, medallion data architecture, and Delta Lake
Ability to learn technical concepts quickly and communicate effectively across functional teams
Ability to own tasks from start to finish with a solution-oriented mindset
Bachelor’s degree in Computer Science or Computer Engineering

Responsibilities

Design, build, and optimize pipelines that turn raw data into meaningful outcomes.
Leverage Databricks, PySpark, and SQL to scale data platforms.
Collaborate within a cross-functional ecosystem spanning Data Engineering, AI/Data Science, Governance, and Reporting.
Integrate new AI technologies and expand DataOps and MLOps capabilities.