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Metadata​/Data Cataloging Analyst

Job in McLean, Fairfax County, Virginia, USA
Listing for: Guidehouse Careers
Full Time position
Listed on 2026-07-22
Job specializations:
  • IT/Tech
    Information & Knowledge Management
Salary/Wage Range or Industry Benchmark: 100000 - 140000 USD Yearly USD 100000.00 140000.00 YEAR
Job Description & How to Apply Below
Position: Metadata / Data Cataloging Analyst

Job Family: Data Engineering & Architecture Consulting

Travel Required: Up to 10%

Clearance Required: Ability to Obtain Public Trust

Job Summary

The Metadata / Data Cataloging Analyst (Senior Consultant) supports enterprise metadata baselining, data catalog tool evaluation, and governance workflow operationalization by executing structured metadata intake, normalization, validation, and evidence‑based documentation across DHA stakeholders. This role is hands‑on: conducting in‑person/virtual interviews with system owners, data stewards, and SMEs to capture and standardize technical, business, operational, and security metadata in catalog‑ready formats; and supporting steward validation cycles to ensure accuracy and completeness.

In addition, this role performs hands‑on evaluation of data catalog solutions as part of an Analysis of Alternatives (AoA), including requirements‑to‑capability mapping, demos, evidence capture, gap documentation, and synthesis of tradeoffs aligned to DHA priorities (e.g., integration, lineage, governance workflows, access/security, usability, and vendor support).

The role also contributes to optional governance and lifecycle pilots by supporting federated stewardship readiness assessments (e.g., role clarity, escalation paths, policy execution, and audit traceability) and by helping define and exercise data product lifecycle workflows (e.g., publication, discovery, change control, versioning, SLA alignment, and deprecation), including measurement of compliance to quality and semantic tagging protocols.

Key Responsibilities
  • Execute structured metadata intake & normalization:
    Conduct in‑person/virtual interviews and working sessions with system owners, data stewards, custodians, and SMEs to elicit, capture, and normalize technical, business, operational, and security metadata; reconcile findings with available artifacts (e.g., inventories, data dictionaries) to produce catalog‑ready metadata records.
  • Standards‑aligned metadata structuring:
    Apply standardized intake templates and ensure metadata is structured in catalog‑ready formats aligned to recognized metadata standards (e.g., ISO/IEC 11179 and DCAT‑US) and schema categories (technical, business, operational, security), including ownership/stewardship and sensitivity indicators as applicable.
  • Steward validation cycles & quality controls:
    Drive completeness/consistency checks, document discrepancies, and coordinate steward validation cycles to confirm definitions, resolve gaps, and improve metadata reliability prior to repository or catalog ingestion.
  • Embedded engagement model:
    Embed with system owners and designated stewards to improve metadata accuracy and completeness, support rapid clarification loops, and ensure metadata reflects real operational usage and constraints.
  • Hands‑on catalog tool evaluation:
    Perform structured evaluation of catalog solutions across discovery, lineage, governance workflows, UX, and APIs; capture evidence through demos and testing; document strengths, gaps, and constraints; and contribute to comparative scoring inputs aligned to requirement taxonomies (functional, integration, infrastructure/compute, access/security, vendor support/cost).
  • AoA workshop and documentation support:
    Support criteria refinement sessions, requirement prioritization inputs, and synthesis of findings into decision‑quality artifacts (e.g., evaluation notes, evidence logs, comparison matrices, and recommendation inputs).
  • Federated governance & workforce readiness pilot support:
    Support pilot experiments with federated stewardship roles; assist in capturing observations and metrics on role clarity, policy execution, escalation paths, stewardship effectiveness, metadata lineage demonstration, and policy audit traceability; contribute to pilot reporting outputs.
  • Data product lifecycle workflow support:
    Help define, test, and refine prototype workflows for data product creation, publication, discovery, change control, versioning, SLA enforcement, and deprecation; support measurement of compliance to data quality rules, role‑based controls, and semantic tagging protocols.
  • Program operations & stakeholder coordination:
    Maintain…
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