This role pays less than
75%
of similar roles. Most pay
$129,624–$211,200
— the shaded band above.
At the midpoint, this role pays about
$127k
versus about
$170k
for comparable roles.
Based on 240 similar postings.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
802 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 783 roles with salary data.
As a Data Engineer, you will join a technical team to lead data engineering activities and build advanced technology solutions for mission-driven projects involving fraud detection, cancer research, and national intelligence. You will be responsible for overseeing the development and deployment of pipelines and platforms that organize disparate data into meaningful formats. Your daily work involves collaborating with AI model engineers and cloud architects to design, implement, and maintain scalable data pipelines while performing exploratory analysis and feature development for AI/ML workloads. You will utilize skills in data normalization, schema development, automated ETL workflows, and data governance practices. The role requires proficiency in monitoring pipeline performance and implementing dashboards for tracking metrics. Required technical competencies include experience with cloud environments like AWS or Azure to support data cleaning and orchestration for complex machine learning systems.
What does a Data Engineer earn?
Median $183138 from 214 postings across 58 companies.
Design, implement, and maintain scalable data pipelines to organize disparate data sources.
Develop automated ETL workflows and processes for large-scale data management.
Validate and normalize datasets while developing appropriate schemas for system integration.
Perform exploratory analysis and feature development specifically for AI/ML workloads.
Implement dashboards and metrics to monitor the performance of data pipelines.
Ensure high-quality, well-governed data flows across operational and research systems.
Coordinate with technical leaders to build mission-aligned infrastructure for complex projects.
What we're looking for
TS/SCI clearance with polygraph is required.
Candidates must have 6+ years of experience as a data engineer.
Applicants must possess a high school diploma and 6+ years of experience, or a bachelor's degree and 4+ years of experience in data normalization and pipelines.
Experience validating or normalizing datasets and developing schemas is required.
Experience building automated ETL workflows and pipelines for data processes is required.
Ability to design, implement, and maintain data pipelines is required.
Knowledge of data governance practices is required.
Experience implementing dashboards and metrics for monitoring data and pipeline performance is required.