Senior Cloud Data Architect

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

MBI (T2)

Job Family:

IT Infrastructure and Operations

Job Qualifications:

Skills:

AWS Big Data, Data Architecture Development, Data Warehousing (DW), Snowflake (Platform)

Certifications:

None

Experience:

10 + years of related experience

US Citizenship Required:

No

Job Description:

At GDIT, we deliver clarity with our cloud solutions and provide meaningful work. Your work will be an important part of transforming our clients for the modern age and help them face any obstacle.

We are seeking a highly skilled Senior Cloud Data Architect to guide the design, architecture, and technical strategy for our enterprise Data Warehouse and Business Object data cloud data environment. This is a senior‑level, customer-facing, high‑visibility role central to our modernization efforts. You will shape the architecture supporting complex data ecosystems, provide leadership across engineering workstreams, and ensure the platform evolves in a scalable, secure, and high‑performing direction.

If you excel at solving complex architectural challenges, driving consistency across teams, and influencing data strategy at scale, this role offers the opportunity to make a significant impact.

HOW A CLOUD DATA WAREHOUSE ARCHITECT WILL MAKE AN IMPACT:

• Design, create, and maintain data architecture artifacts

• Create and maintain an architectural roadmap for the Data Management and Analytics capabilities including support for generative and agentic AI

• Architect enterprise‑level Snowflake data warehouse solutions, including conceptual, logical, and physical models that support analytics, operational reporting, modernization and AI initiatives

• Provide technical leadership across multiple teams, ensuring architectural alignment and model‑driven engineering throughout ETL/ELT pipelines

• Define data architecture patterns, standards, and best practices to ensure consistency, scalability, and performance across the platform

• Lead design decisions related to schema architecture, data distribution, performance optimization, security, governance, and cost management in Snowflake

• Collaborate with Program Management, Agile PMO, ETL development, DevSecOps, DBA, user support, and analytics teams to guide solution design and ensure alignment with enterprise and customer goals

• Oversee ingestion, transformation, and integration of complex healthcare datasets, ensuring data quality and metadata completeness

• Work hands-on in Snowflake, including DDL design, warehouse configuration, performance tuning, and workload optimization

• Leverage and advise on usage of related AWS data services (e.g., Lambda, S3, Glue, Step Functions, IAM) to support end‑to‑end data pipelines

• Guide automation approaches for data integration, testing, metadata capture, lineage, and platform operations

• Assess and troubleshoot high-complexity issues, providing direction and technical resolutions across teams

• Support roadmap planning by providing architectural insight, identifying technical risks, and shaping long-term data strategy

• Mentor and develop data engineers, administrators and modelers, setting the technical tone and raising capability across the program

• May serve as a technical lead and/or manager over multiple cloud data engineers / teams

WHAT YOU’LL NEED TO SUCCEED:

Required Education:

• BS degree

Required Experience:

• 10 years of experience in cloud data architecture, data warehousing, data modeling and data analytics in a complex data environment

• Required Technical Skills:

• Extensive hands-on Snowflake experience, with strong skills in implementing logical and physical models, and leveraging Snowflake tools, including Cortex AI.

• Proven leadership in large-scale cloud data environments, preferably within AWS

• Deep experience with ETL/ELT frameworks and model‑driven engineering approaches

• Proficiency in SQL, data transformation design, and performance optimization

• Experience working with cloud‑native architectures, modern data integration patterns and AI solution development

• Strong expertise in automation and scripting (e.g., Bash, PowerShell, Python, PySpar