Cloud Data Engineer
Quick Summary
Skills:Data Flows, Data Structures, Data Warehousing (DW),
Clearance Level Must Currently Possess:
NoneClearance Level Must Be Able to Obtain:
NoneJob Family:
Data Science and Data EngineeringRequirements
~1 min readJob 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.
- 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.
- 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.
- 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, AWS CLI, Snowflake).
- Experience with ETL tools
What We Offer
~1 min readWork Location:
Any Location / RemoteAdditional Work Locations:
Location & Eligibility
Listing Details
- Posted
- October 2, 2026
- First seen
- October 2, 2026
- Last seen
- October 4, 2026
Posting Health
- Days active
- 1
- Repost count
- 0
- Trust Level
- 65%
- Scored at
- October 4, 2026
Signal breakdown
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