Data Quality Automation Engineer

Booz Allen Hamilton; Hampton (VA); On-site; USD 62,000 - 141,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Paid leave

Professional development

Tuition assistance

Work-life programs

Dependent care

Job summary

Booz Allen Hamilton is seeking a Cyber Automation Engineer/Data Quality Engineer in the United States to ensure data integrity across systems. You will develop automated validation, reconcile data, and collaborate with a cross-functional team in an Agile environment.

Responsibilities include building Python scripts for validation, verifying records across environments, retesting fixes, and communicating data health metrics.

Qualifications

• Experience programming with Python for data manipulation, validation, and automation.
• Proficiency with SQL and relational databases.
• Experience with APIs and handling JSON/XML/CSV formats.
• Knowledge of Git and CI/CD concepts.
• Ability to work in an Agile environment.

Responsibilities

• Develop, maintain, and execute automated validation and data reconciliation scripts.
• Investigate, analyze, and document data discrepancies and anomalies.
• Verify that system records are created, updated, and maintained correctly across environments.
• Retest data fixes and validate resolutions implemented by the development team.
• Communicate findings, data health metrics, and quality reports clearly to a cross‑functional team.
• Participate in Agile ceremonies such as sprint planning, daily stand-ups, and retrospectives.

Skills

Python programming

SQL

APIs

Git & CI/CD

Agile environment

Education

Bachelor's degree

Tools

pandas

NumPy

Jira or GitLab

Power BI

C# & .NET

Job description

Booz Allen Hamilton is seeking a Cyber Automation Engineer/Data Quality Engineer in the United States to ensure data integrity across systems. You will develop automated validation, reconcile data, and collaborate with a cross-functional team in an Agile environment.

Responsibilities include building Python scripts for validation, verifying records across environments, retesting fixes, and communicating data health metrics.