This role pays less than
88%
of similar roles. Most pay
$143,697–$202,911
— the shaded band above.
At the midpoint, this role pays about
$127k
versus about
$173k
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.
Data Engineer, Senior joins a multi-disciplinary team in an agile environment to develop advanced technology solutions and manage the assessment, design, building, and maintenance of scalable platforms. The role involves deploying pipelines and platforms that organize disparate data into meaningful insights for mission-driven projects involving fraud detection, cancer research, and national intelligence. Key responsibilities include designing data warehouses or lakes, developing RESTful API models, and automating large-scale batch and streaming data workflows. Candidates will utilize SQL, Python, Scala, Spark, or Java to manage data lifecycle management and governance policies. The technical stack includes AWS EMR, AWS Glue, Azure Data Factory, Databricks, Snowflake, Redshift, BigQuery, and NoSQL databases like MongoDB or Elasticsearch. Required expertise includes tuning cloud storage, managing CI/CD pipelines via Jenkins or GitHub, and navigating federal information system policies such as NIST 800.53.
What does a Data Engineer earn?
Median $183138 from 214 postings across 58 companies.
Design and develop scalable ETL/ELT data pipelines for batch and streaming workflows.
Build and maintain data warehouse and data lake architectures using SQL, Python, Spark, or Java.
Develop platforms to organize and process structured, unstructured, and event-streaming data.
Perform tuning on data lake architecture to optimize cloud storage and pipeline performance.
Manage data governance policies including cataloging, usage tracking, and lifecycle management.
Implement automated CI/CD pipelines across multiple technical stacks.
Architect large-scale enterprise data systems using AWS or Microsoft Azure cloud products.
Develop and manage AI and machine learning pipelines for mission-critical projects.
What we're looking for
Top Secret clearance.
Bachelor’s degree and 6+ years of experience designing, developing, operationalizing, and maintaining data systems, or 10+ years of experience in lieu of a degree.
5+ years of experience designing data warehouse or data lake, RESTful API models, event processing, or business intelligence for software systems.
5+ years of experience building scalable ETL/ELT pipelines, automating large-scale batch and streaming workflows, and parsing structured or unstructured data.
5+ years of experience coding in SQL, Python, Scala, Spark, or Java.
Experience performing tuning on data lake architecture to optimize cloud storage and pipeline performance.
Experience with data management solutions for data catalog, usage, governance policies, and lifecycle management.
Experience with AWS/Azure products, distributed tools (Spark, NiFi, AirFlow), NoSQL databases, AI/ML pipelines, or federal information system policies (preferred).