This role pays less than
80%
of similar roles. Most pay
$139,400–$205,950
— 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
821 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 799 roles with salary data.
As a Databricks Platform Engineer, you will join a cross-functional team of over seventy people spanning data engineering, AI, and science to design, build, and optimize infrastructure and DataOps workflows for a high-impact Fortune 500 client program. You will be responsible for scaling and governing data environments while driving CI/CD automation, ensuring platform observability, managing cloud budgets, and integrating new AI capabilities. Your daily work involves utilizing Databricks, Python, SQL, Terraform, and Terragrunt to manage infrastructure. You will also leverage GitHub Actions, Splunk, or Dynatrace for monitoring and logging. The role focuses on solving complex platform challenges related to scalability, cost-efficiency, and governance within a distributed processing environment. Key technical components include Unity Catalog administration, Delta Lake architecture, and the integration of MLOps capabilities to support advanced data analytics.
3+ years of experience configuring Databricks components, prioritizing Unity Catalog administration, workflows, and Delta Lake architecture (preferred).
Experience with Python, SQL, Scala, or Java (preferred).
Experience scaling AI workloads, integrating new AI technologies, and supporting MLOps capabilities (preferred).
Experience working in an Agile development environment (preferred).
Ability to assist in implementing budget controls and optimizing compute costs across Databricks and cloud resources (preferred).
Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field (preferred).