Data Architect-Enterprise Data Analyst

Data Architect / Enterprise Data Analyst

The Data Architect / Enterprise Data Analyst will provide data strategy, architecture, and analytics expertise to support enterprise data initiatives across the U.S. Department of Health and Human Services (HHS). This role will define and implement data architecture frameworks, data governance standards, and enterprise data management (EDM) solutions to improve data quality, accessibility, security, and interoperability across systems and organizations. The ideal candidate will have experience working in federal data environments, including designing enterprise data models, developing data integration strategies, and supporting data modernization and cloud migration projects. The role also requires strong collaboration skills to work with IT leadership, system owners, data stewards, and mission stakeholders to enable informed decision-making through trusted and well-governed data. Key Responsibilities

Data Architecture & Strategy Develop and maintain enterprise data architecture strategies, standards, and roadmaps aligned with HHS mission and federal data policies. Lead design of conceptual, logical, and physical data models for enterprise systems and data warehouses. Support modernization efforts by designing scalable, secure cloud-based data solutions (AWS, Azure, or GCP). Define and enforce data architecture principles, metadata standards, and integration patterns across systems. Recommend improvements to data storage, access, and reporting solutions to support enterprise analytics capabilities. Enterprise Data Management Establish enterprise data governance frameworks including data ownership, stewardship, metadata, and lineage strategies. Identify and address data quality issues by defining validation rules, profiling datasets, and implementing quality controls. Support Master Data Management (MDM) and data catalog efforts to improve consistency and discoverability of enterprise data. Develop enterprise data dictionaries, metadata repositories, and system documentation. Data Integration & Analytics Design and support ETL/ELT processes using tools such as Informatica, Talend, Azure Data Factory, or AWS Glue. Collaborate with BI teams to deliver enterprise dashboards, reports, and data visualizations in Power BI, Tableau, or Qlik. Integrate and align data from multiple systems, including ERP, HR, grants, finance, and program datasets. Support data interoperability initiatives using APIs, service buses, and data sharing platforms. Stakeholder Engagement & Collaboration Work with HHS program offices, business analysts, data owners, and architects to understand business priorities and translate them into data capabilities. Serve as a trusted advisor for data strategy, stewardship, and data-driven decision-making. Facilitate data workshops, governance meetings, and working sessions with technical and non-technical stakeholders. Support project planning, requirements analysis, and solutions development within Agile or SDLC frameworks. Qualifications and Skills

U.S. Citizen

with the ability to obtain and maintain a

Public Trust clearance . Bachelor's degree

in Information Systems, Data Science, Computer Science, or related field. 8+ years of experience

in data architecture, enterprise data analysis, or data engineering. Experience developing

enterprise data models, data dictionaries, and metadata standards . Strong hands-on experience with

SQL

and relational databases (Oracle, SQL Server, PostgreSQL). Experience with

ETL/ELT tools

and

data integration techniques . Familiarity with

cloud-based data platforms

(AWS, Azure, or GCP). Knowledge of

data governance frameworks

and data quality best practices. Excellent communication skills, especially in complex federal environments. Desired Skills and Competencies

Experience supporting

HHS

or other federal health agencies (CMS, NIH, HRSA, FDA, CDC). Familiarity with

federal data policies

such as the Federal Data Strategy and CDO requirements. Experience with

enterprise data warehouses

or

data lakes . Certifications such as

CDMP, AWS Data Analytics, Azure Data Engineer, or DAMA . Knowledge of

FHIR, HL7, NIEM

or federal data interoperability standards. Experience with

API integrations, service-oriented architecture (SOA), or microservices . Flexible work from home options available.