Data Engineer

Booz Allen Hamilton•Honolulu, HI

2d•$61,900 - $141,000•Onsite

About The Position

As a data engineer at Booz Allen, you’ll use your skills and experience to help build advanced technology solutions and implement data engineering activities on some of the most mission-driven projects in the industry. You’ll develop and deploy the pipelines and platforms that organize and make disparate data meaningful. Here, you’ll work with a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll sharpen your skills in analytical exploration and data examination while you support the assessment, design, developing, and maintenance of scalable platforms for your clients. Work with us to use data for good. Join us. The world can’t wait.

Requirements

2+ years of experience utilizing programming languages, including C++, Java, or Python
2+ years of experience developing and maintaining scalable data stores that supply big data in forms needed for business analysis
Experience creating software for retrieving, parsing and processing structured and unstructured data
Experience with developing scalable ETL and ELT workflows for reporting and analytics
Experience creating solutions within a collaborative, cross-functional team environment
Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms
Secret clearance
Bachelor’s degree

Nice To Haves

Experience working with Palantir Foundry
Experience in application development utilizing SQL or Scala
Experience working on real-time data and streaming applications
Experience with NoSQL implementation using MongoDB or Cassandra
Experience with data warehousing, including AWS Redshift, MySQL, or Snowflake
Experience with UNIX or Linux, including basic commands and Shell scripting
Experience with Agile engineering practices
TS/SCI clearance with a polygraph

Responsibilities

Develop and deploy pipelines and platforms that organize and make disparate data meaningful.
Support the assessment, design, developing, and maintenance of scalable platforms for clients.
Develop scripts and programs for converting various types of data into usable formats.
Support project teams to scale, monitor, and operate data platforms.