Data Engineer (Data Quality & Automation)

Analytica•Bethesda, MD

About The Position

Analytica is seeking a Data Engineer with experience in automated data quality validation and CI/CD-enabled data pipelines to support a long‑term federal government program. The ideal candidate will be responsible for designing, developing, and maintaining reliable data pipelines while embedding data quality, validation, and automation practices directly into the data engineering lifecycle. This role supports enterprise data platforms and products within a DevSecOps framework and works closely with data engineers, analytics engineers, architects, and other stakeholders to ensure data solutions are scalable, reliable, and production‑ready.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent experience.
Experience supporting data pipelines in a DevOps or DevSecOps environment.
5+ years of experience in data engineering, ETL development, or related roles.
Strong experience with Microsoft SQL Server and enterprise data warehouse or data lake platforms.
Proficiency in Python or similar scripting languages for automation.
Hands‑on experience building and supporting ETL/ELT pipelines.
Experience implementing automated data validation or data quality checks within data pipelines.
Familiarity with CI/CD concepts and tools as applied to data engineering workflows.
Strong analytical and problem-solving skills.
Excellent written and verbal communication skills.
Must be a U.S. Citizen with the ability to obtain a secret clearance.

Nice To Haves

Experience working in cloud environments (AWS, Azure, or GCP).
Experience supporting analytics, reporting, or data mart solutions.
Experience supporting data modeling solutions (i.e. Kimball).
Prior experience supporting Defense Health Agency - DHA and Military Health Services - MHS data programs.
Current active secret clearance

Responsibilities

Design, develop, and maintain ETL/ELT data pipelines supporting enterprise data platforms.
Implement and enhance data ingestion, transformation, and integration processes using SQL and modern programming languages.
Design and implement automated data quality and validation checks (e.g., schema integrity, completeness, freshness, volume).
Embed data validation and testing logic directly into data pipelines and CI/CD workflows.
Refactor and modernize existing data pipelines to improve reliability, performance, and maintainability.
Collaborate with technical leads, architects, and engineering teams to define and promote standard data engineering and quality practices.
Support deployment, monitoring, and troubleshooting of data pipelines across development, test, and production environments.
Contribute to technical documentation, runbooks, and reusable components to improve team efficiency and consistency.
Participate in design and code reviews with a focus on sustainability, automation, and operational excellence.