Data Success Engineer

Booz Allen Hamilton•Bethesda, MD

4h•$77,600 - $176,000•Hybrid

About The Position

As a Data Success Engineer, you will work at the intersection of business analysis and data engineering to turn client needs into reliable, usable data products. You will partner with business stakeholders, data owners, analysts, and technical teams to understand business processes and data needs, clarify requirements, and build or improve data-delivery pipelines. Using SQL and Python, you will query, profile, transform, and validate data, troubleshoot quality issues, and help ensure solutions meet business requirements. You will document data definitions and transformation logic, explain technical findings clearly, contribute to Agile planning and continuous improvement, support solutions built with Databricks, and help clients understand how data products support business outcomes. The role is hybrid, with work at a Booz Allen or customer facility in alignment with leadership expectations and role needs. Applicants selected will be subject to a government investigation and may need to meet U.S. government client eligibility requirements. The position requires the ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.

Requirements

Experience gathering, analyzing, and documenting business or data requirements, including translating needs into user stories, acceptance criteria, source-to-target mappings, or technical specifications.
Experience working directly with clients and stakeholders to facilitate information-gathering discussions, ask effective questions, clarify needs, and communicate findings.
Experience with SQL, including writing complex queries and investigating data issues across multiple tables or sources.
Experience using AWS services, including AWS Glue, Amazon S3, and Amazon RDS.
Experience using Python for data processing, automation, or pipeline development.
Experience working with relational databases and structured data.
Ability to connect business objectives to data requirements and technical implementation.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
Bachelor’s degree in Computer Science, Computer Engineering, Engineering, Math, Physics, or Information Systems and Technology.

Nice To Haves

Experience with Databricks, including notebooks, Spark, Delta Lake, or Databricks SQL.
Experience with data warehousing, lakehouse architecture, or medallion data architecture.
Experience with data quality frameworks, metadata management, or data governance.
Experience with Agile delivery tools and practices, such as Jira, Confluence, and Scrum.
Experience creating process flows, data models, or other artifacts that help teams understand how data moves and is used.
Strong analytical, problem-solving, written, and verbal communication skills.
Databricks, AWS, or data engineering certifications.

Responsibilities

Partner with business stakeholders, data owners, analysts, and technical teams to understand business processes and data needs.
Gather, clarify, and translate client needs into business and data requirements.
Build or improve pipelines that deliver data.
Use SQL and Python to query, profile, transform, and validate data.
Troubleshoot data quality issues and help ensure solutions meet business requirements.
Document data definitions and transformation logic.
Explain technical findings in clear language.
Contribute to Agile planning and continuous improvement.
Support solutions built with Databricks.
Help clients understand how data products support business outcomes.
Facilitate information-gathering discussions with clients and stakeholders and communicate findings.