Data Analyst
Job in
Washington, District of Columbia, 20022, USA
Listed on 2026-08-20
Listing for:
Guidehouse
Full Time
position Listed on 2026-08-20
Job specializations:
-
IT/Tech
Data Engineering, Data Analyst, Business Systems & Technology Analysis, Data Warehousing
Job Description & How to Apply Below
Data Science & Analysis
Travel Required:
Up to 10%
Clearance Required:
Ability to Obtain Public Trust
Job Description Summary The Data Analyst – Solution Architecture Support will provide analytical, documentation, data modeling, and data-driven decision support for a large-scale agile software development and platform modernization program supporting the Grant Solutions contract. This role will work closely with the Solution Architect, Product Owners, engineering teams, enterprise architects, data architects, vendors, and Federal stakeholders to analyze current-state processes, data flows, interface dependencies, data models, reporting needs, and modernization impacts.
The Data Analyst will help translate business and technical information into clear artifacts that support architecture decisions, integration planning, data governance, release readiness, data model alignment, and long-term platform modernization objectives.
What You Will Do:
We are seeking a detail-oriented Data Analyst to support the Solution Architect on a large-scale Grant Solutions platform modernization effort. This role will help analyze business processes, data structures, conceptual and logical data models, system interfaces, reporting needs, and modernization dependencies to inform solution design and technical execution across multiple work streams, vendors, and Scrum teams.
The Data Analyst will support the Solution Architect by gathering, analyzing, validating, modeling, and documenting data and process information needed to guide modernization decisions. This individual will develop clear analysis artifacts, data mappings, data model views, entity relationship summaries, interface inventories, workflow summaries, decision support materials, and stakeholder-ready documentation. The role requires strong analytical thinking, attention to detail, communication skills, and the ability to work collaboratively with technical and non-technical stakeholders to support architecture alignment, data quality, data modeling, integration planning, governance, and incremental transition from legacy capabilities to modernized services.
Support the Solution Architect by analyzing current-state processes, data flows, system interfaces, reporting needs, and modernization dependencies across legacy and modernized capabilities.
Develop and maintain data mapping artifacts, conceptual and logical data model views, entity relationship summaries, interface inventories, source-to-target documentation, process flows, dependency logs, and analysis summaries that inform architecture and implementation decisions.
Gather and validate business, data, and reporting requirements from Product Owners, Federal stakeholders, vendors, subject matter experts, and delivery teams.
Analyze data quality, data lineage, system-of-record considerations, duplicate data paths, synchronization needs, data model alignment, and integration impacts to support modernization planning.
Support development and validation of conceptual, logical, and implementation-oriented data models by identifying key entities, relationships, attributes, business rules, data domains, and model impacts across legacy and modernized capabilities.
Translate complex business and technical information into clear documentation, visuals, decision summaries, briefing materials, and stakeholder-ready analysis products.
Support architecture review, design discussions, trade-off analysis, release readiness reviews, and dependency management by preparing evidence-based analysis and concise summaries.
Coordinate with engineering, testing, Dev Sec Ops , data, security, and vendor teams to confirm assumptions, clarify data needs, document open questions, and track follow-up actions.
Assist with analysis of API-enabled services, shared platform capabilities, data exchange patterns, workflow automation, interoperability needs, and legacy coexistence considerations.
Identify and communicate risks, gaps, inconsistencies, and dependencies related to data, interfaces, workflows, requirements, reporting, testing, and operational transition planning.
Maintain organized analysis repositories, working documents,…
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