Data Engineer and Data Scientist

Booz Allen Hamilton•Arlington, VA

1d•$62,000 - $141,000

About The Position

As a data engineer at Booz Allen, you will help clients find insights in structured and unstructured data to support missions such as fraud detection, cancer research, and national intelligence. You will build advanced technology solutions and perform data engineering activities on mission-driven projects, developing and deploying pipelines and platforms that organize data from disparate sources and make it useful. You will work with analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. The role includes supporting the assessment, design, development, and maintenance of scalable client platforms, while applying analytical exploration and data examination skills.

Requirements

At least 2 years of experience using programming languages including Python, SQL, and R.
At least 2 years of experience developing and maintaining scalable data stores for business analysis.
Experience developing scalable ETL or ELT workflows for reporting and analytics.
Experience with Databricks.
Ability to manage large structured, semi-structured, and unstructured datasets while ensuring data quality, security, and governance.
Ability to develop and manage data pipelines supporting enterprise-level analytics, reporting, and machine learning projects.
Ability to develop scripts and programs that convert data into usable formats and support teams in scaling, monitoring, and operating data platforms.
Secret clearance required.
Bachelor’s degree.

Nice To Haves

Experience with the War Data Platform.
Experience with distributed data or computing tools such as Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka.
Experience working on real-time data and streaming applications.
Experience with Agile engineering practices.
Ability to contribute to data modeling, feature engineering, and other pre-processing work for advanced analytics.
Ability to support exploratory data analysis on large datasets to identify trends, patterns, and actionable insights.
TS/SCI clearance.

Responsibilities

Build advanced technology solutions and implement data engineering activities on client projects.
Develop and deploy pipelines and platforms that organize disparate data and make it meaningful.
Support the assessment, design, development, and maintenance of scalable platforms.
Develop and maintain scalable data stores that supply data in forms needed for business analysis.
Develop scalable ETL or ELT workflows for reporting and analytics.
Manage and organize large structured, semi-structured, and unstructured datasets while ensuring data quality, security, and governance.
Develop and manage data pipelines for enterprise analytics, reporting, and machine learning projects.
Develop scripts and programs to convert data into usable formats.
Support project teams in scaling, monitoring, and operating data platforms.
Support analytical exploration and data examination.