Data Engineer

Booz Allen Hamilton•McLean, VA

7d•$77,600 - $176,000

About The Position

As a data engineer at Booz Allen, you’ll help build advanced technology solutions and implement data engineering activities on some of the most mission-driven projects in the industry. You’ll deploy and develop pipelines and platforms that organize and make disparate data meaningful. You’ll work with and guide a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for your clients. Work with us to use data for good.

Requirements

2+ years of experience creating software for retrieving, parsing, and processing structured and unstructured data
Experience with Python, SQL, Scala, or Java
Experience building scalable ETL and ELT workflows for reporting and analytics
Experience creating solutions within a collaborative and cross-functional team environment
Knowledge of version control tools such as GitLab, GitHub, or Bitbucket
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
HS diploma or GED

Nice To Haves

Experience with UNIX or Linux, including basic commands and Shell scripting
Experience with a public cloud, including AWS, Microsoft Azure, or Google Cloud
Experience with distributed data or computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka
Experience with NoSQL implementation, including MongoDB or Cassandra
Experience with Databricks
Experience with data warehousing using AWS Redshift, MySQL, or Snowflake
Bachelor's degree
Security+ Certification

Responsibilities

Deploy and develop pipelines and platforms that organize and make disparate data meaningful.
Manage the assessment, design, building, and maintenance of scalable platforms for clients.
Create software for retrieving, parsing, and processing structured and unstructured data.
Build scalable ETL and ELT workflows for reporting and analytics.
Develop scripts and programs for converting various types of data into usable formats.
Support project teams to scale, monitor, and operate data platforms.