Master & Reference Data Management Analyst

Master & Reference Data Management (MDM/RDM) AnalystContract|Fully RemoteAbout the RoleMaster and reference data become trustworthy through profiling cycles, steward reviews, hierarchy maintenance, and the disciplined operational work that keeps a domain healthy day after day. That is the work the Master Data Management (MDM) Analyst owns. As the client places Master Data and Reference Data Specialists into client AI Governance and semantic layer engagements, we staff MDM Analysts alongside them to operationalize the domain-level work — profiling, match candidate review, reference data sourcing, hierarchy curation, and stewardship support.As AI workflows increase the need for trusted master and reference data, the Analyst role has expanded: stewards need help capturing data definitions, match outcomes need to be reviewed and approved, and AI-specific data assets (training datasets, feature inputs) require the same governance discipline as traditional master data. This role is consistently busy across our client portfolio.Key ResponsibilitiesMeeting Facilitation Support: Participate in and document meetings, workshops, and interviews with business and IT stakeholders; capture decisions, action items, and requirements.Profiling and Analysis: Run profiling against master and reference data assets; document patterns, anomalies, and quality gaps; support root-cause analysis with stewards.Match and Merge Support: Review match candidates with stewards, document survivorship outcomes, and contribute to ongoing tuning of match and merge rules.Reference Data Operations: Support sourcing of external reference standards, manage internal reference sets, and track standard updates and distribution to consuming systems.Hierarchy Maintenance: Support the curation of domain hierarchies; reconcile change requests with stewards and capture approvals.Stewardship Support: Help onboard data stewards under the Specialist's direction; document responsibilities and coach stewards through their early cycles of activity.Quality Operations: Help define and monitor data quality rules for master and reference data; track remediation work and produce metrics for engagement leadership.Tool Operations: Operate within the client's MDM and RDM platform for day-to-day work (tool-agnostic — Informatica MDM, Reltio, SAP MDG, Profisee, Stibo STEP, IBM MDM, Talend, Oracle CDM, or other).Deliverable Production: Prepare profiling reports, runbooks, training materials, presentations, and other client-ready deliverables to the client's standards.Required Qualifications3+ years of experience as a Business Analyst, Data Analyst, or MDM/RDM Analyst supporting master data, reference data, or data quality programs.Hands-on data profiling and analysis experience; SQL proficiency.Working knowledge of core MDM concepts — match and merge, survivorship, golden record, hierarchy management.Ability to pull together disparate information — across topics, formats, and levels of detail — and distill it into clear insights, narratives, and recommendations.Working knowledge of the reference data lifecycle — sourcing, ingestion, customization, and distribution of internal and external standards.Preferred QualificationsHands-on experience with at least one MDM platform (Informatica MDM, Informatica MDM 360, Reltio, SAP MDG, Profisee, Stibo STEP, IBM MDM, Talend, Oracle CDM) or experience operating as a master data steward.Exposure to AI/ML data preparation work, feature inputs, training data curation, or AI-grounding reference standards.Familiarity with industry reference standards relevant to the candidate's domain, LEI, ISIN, CUSIP for financial services; UNII, RxNorm, SNOMED, HCP/HCO structures for life sciences and healthcare; UNSPSC for product.Exposure to ML-based matching or entity resolution approaches.Familiarity with adjacent data quality tooling (dbt tests, Great Expectations, Soda, Monte Carlo, Bigeye).Industry experience in life sciences, financial services, healthcare, insurance, or other regulated environments.Familiarity with frameworks such as DAMA-DMBOK or DCAM.Exposure to semantic layer concepts (taxonomies, conformed dimensions, ontologies) and how master and reference data anchor them.What Success Looks LikeBy the end of a successful engagement, mapped to our client's General Project Methodology, the Master Data Management Analyst’s work may include:Produce a body of high-quality client deliverables across the methodology phases — profiling output, match and merge documentation, reference data runbooks, training materials, status reports.Support the Master Data and Reference Data team in delivering operational master and reference data capabilities in the assigned domain(s).Sustain the operating cadence for the domain — profiling cycles, steward review meetings, hierarchy reconciliation, status reporting.Contribute to AI and ML data documentation where in scope, including training data lineage and feature input documentation.Build measurable client capability so analyst-level operations continue post-engagement.