Data Architect (W2)

Specialized experience in Developing enterprise data strategies and target-state architectures. Directing the migration of legacy data silos into modern enterprise platforms.
Advise the agency''s data governance program, ensuring data is treated as a strategic enterprise asset with clear accountability, quality standards, and lifecycle management
Lead the strategic planning and architectural design of data modernization initiatives, directing the migration of disparate legacy data silos into integrated, modern enterprise data platforms
Serve as the agency''s foremost authority on data modeling concepts, principles, and methodologies, providing architectural direction and design standards for the evolution of enterprise data structures
Provide strategic thought leadership and expert technical guidance on data management to all levels of the organization, building data literacy and a culture of data-driven decision-making
Establish and maintain enterprise-level change management and configuration control programs governing all data architecture and data structure changes across the agency
Complete the initial online assessment and USAHire Assessment, if required
 Skills needed
Data architecture & modeling: Strong experience designing enterprise data models (conceptual/logical/physical), including dimensional modeling (star/snowflake) and normalized models; ability to translate business needs into scalable data structures.
Azure Data Plaform: Azure Data Platform: Expertise architecting and supporting solutions across Microsoft’s cloud data ecosystem, including Microsoft Fabric (data engineering, lakehouse, pipelines), Azure SQL, and Data Lake, with strong proficiency in data governance, cataloging, lineage, and security using Microsoft Purview.
Microsoft SQL Server: Deep knowledge of MS SQL Server (T-SQL, schema design, indexing, query performance tuning, security, and operational best practices).
Data integration / ETL: Experience building and managing pipelines using SSIS (or equivalent ETL/ELT tooling), including orchestration, monitoring, and error handling.
BI / Semantic layer: Experience designing and supporting analytics solutions using SSAS (Tabular) and/or equivalent semantic modeling; understanding of measures, hierarchies, and reusable data sets.
Reporting & visualization: Hands-on experience with Power BI (data modeling, DAX fundamentals, dataset governance) and/or SSRS for operational reporting.
Master Data Management: Experience with MDS or another MDM/master data tool and concepts (golden record, survivorship, reference data, stewardship workflows).
Data governance & quality: Practical experience implementing data standards, lineage/metadata practices, data quality controls, and access/security patterns.
Communication & stakeholder management: Ability to partner with technical and non-technical stakeholders, document architecture decisions, and guide teams toward consistent implementation.