Cloud Data Engineer

GDIT is a global technology and professional services company delivering technology solutions and mission services to government, defense, and intelligence organizations. The Principal Cloud Data Engineer will design and lead scalable data solutions supporting CMS healthcare programs, including efforts to combat fraud, waste, and abuse. The role also provides technical guidance, oversees testing and project initiatives, and improves data quality and workflow automation.

Responsibilities:

• 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

Requirements:

• Data Flows, Data Structures, Data Warehousing (DW), ETL Processing
• 8 + years of related experience
• No
• • 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
• • Data modeling, and source‑to‑target mappings
• • Developing with serverless architectures and microservices
• • Strong Linux and CLI skills (bash, AWS CLI, Snowflake)
• • Experience with ETL tools
• • 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
• • Knowledge of Kimball and Inmon data warehouse methodologies