Cloud Data Engineer

Type of Requisition:
Regular
Clearance Level Must Currently Possess:
None
Clearance Level Must Be Able to Obtain:
None Public Trust/Other Required:
None
Job Family:
Data Science and Data Engineering Job Qualifications:
Skills:
Data Flows, Data Structures, Data Warehousing (DW), ETL Processing Certifications:
None Experience:
8 + years of related experience US Citizenship Required:
No
Job Description:

Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As a Data Engineer Principal at GDIT, you’ll power innovation to drive mission impact and grow your expertise to power your career forward.

As a Data Engineer Principal, the work you’ll do at GDIT will be impactful to the mission of the Centers for Medicare and Medicaid Services (CMS). You will play a crucial role in helping combat fraud waste and abuse in healthcare programs.
HOW A DATA ENGINEER PRINICPAL WILL MAKE AN IMPACT:

- Design, build, test, debug, and document scalable data solutions, delivering enhancements for both new and existing systems.

- Conduct thorough unit and integration testing to ensure solutions meet functional and stakeholder requirements.

- Provide expert technical guidance, supporting high‑level solution architecture, planning, and cost estimation activities.

- Lead project initiatives, driving development efforts and ensuring requirements, milestones, and timelines are consistently met.

- Partner with end‑user analysts to define, refine, and optimize Data Warehouse requirements.

- Collaborate with business analysts to validate test plans, test cases, and overall solution quality.

- Drive continuous improvement by identifying opportunities to streamline processes, enhance data quality, and strengthen workflow automation.

WHAT YOU’LL NEED TO SUCCEED

- Bachelor’s degree in a relevant field.

- 8+ years of hands-on experience in data engineering or related disciplines.

- Proficiency with scripting and programming languages such as Python, shell scripting, SQL, and JavaScript.

- Experience building decoupled, scalable data pipelines.

- Strong data warehouse skills; Snowflake experience preferred.

- Hands-on CI/CD experience promoting code across development, test, and production environments.

- Use of Git-based repositories and AWS deployment pipelines (Bitbucket, CodeCommit, GitHub).

- Experience designing and implementing job scheduling and orchestration workflows.

- Solid understanding of data quality principles, including audit, balance, and control.

- Knowledge of data structures, data types, and built-in database functions.

- Experience with bulk file ingestion and processing.

- Data governance experience, including access controls and role-based security.

- Understanding of AWS IAM roles and their integration with AWS native services.

- Experience with AWS data services and event-driven automation (SQS, Lambda, triggers, etc.)

- Experience with Atlassian tools such as Jira and Confluence.

- Experience working in Agile/Scrum environments.

- Strong communication and collaboration skills.

- Self‑starter who contributes ideas for continuous improvement.

- Takes ownership of work and processes; proactive in resolving issues and customer inquiries.

- Ability to learn new technologies quickly and remove obstacles with minimal guidance.

- Collaborates effectively with all stakeholders.

- Self‑driven, accountable, and focused on delivering high‑quality results.

DESIRED SKILLS AND ABILITIES:

- Healthcare claims experience.

- Understanding of data structures.

- Experience with AI solutions to detect data or processing defects.

- Experience with Notebooks (i.e. Jupyter, Snowflake).

- Knowledge of partitions and clustering to improve efficiency and cost.

- Data modeling, and source‑to‑target mappings.

- Developing with serverless architectures and microservices.

- Knowledge of Kimball and Inmon data warehouse methodologies.

- Strong Linux and CLI skills (bash, A