Data Science Engineer

Booz Allen Hamilton•McLean, VA

3d•$77,600 - $176,000•Remote

About The Position

As a Data Science Engineer, you’ll help build advanced technology solutions and implement data science and engineering activities on some of the most mission-driven projects in the industry. You’ll deploy and develop workflows, pipelines, and platforms that organize and make disparate data meaningful, turning these complex data sets into useful information to solve global challenges. Here, you’ll work with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced and agile environment. As a Data Science Engineer at Booz Allen, you’ll also use your passion to master new tools and techniques and identify needed system improvements. You’ll help clients overcome their most difficult challenges using the latest architectural approaches, tools, and technologies, make sure the solution developed by the team considers the current architecture and operating environment, as well as future functionality and enhancements. Work with us as we shape systems for the better. Join us. The world can’t wait.

Requirements

4+ years of experience with python, SQL, ETL, and data pipelines
Experience with containers or container orchestration technologies, such as Kubernetes
Experience with data engineering concepts and implementations
Experience writing source code for new applications or generating and enhancing code samples for existing applications
Experience creating solutions to complex problems within a collaborative and cross-functional team
TS/SCI clearance with a polygraph
Bachelor's degree

Nice To Haves

1+ years of experience with Spark, containerization, ELK, or OpenSearch
Experience acquiring client requirements and designing and recommending solutions based upon these requirements
Experience with AWS technologies, including AWS or S3
Experience with infrastructure as code languages, such as Terraform

Responsibilities

Deploy and develop workflows, pipelines, and platforms that organize and make disparate data meaningful.
Turn complex data sets into useful information to solve global challenges.
Work with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced and agile environment.
Master new tools and techniques and identify needed system improvements.
Help clients overcome their most difficult challenges using the latest architectural approaches, tools, and technologies.
Ensure the solution developed by the team considers the current architecture and operating environment, as well as future functionality and enhancements.