Sr Master Data Management Analyst

Varsity Brands•Farmers Branch, TX

3d•Onsite

About The Position

The Sr. Master Data Management Analyst serves as the connective tissue between business stakeholders and technical teams with a strong hands-on focus on Master Data Management (MDM). This individual is not just a coordinator or advisor, but a deeply technical, data-oriented practitioner who understands how master data is structured, governed, connected, and operationalized across the enterprise. The role is vertically specialized in MDM, with a strong grasp of taxonomy design, entity modeling, master–reference data relationships, data connectivity across systems, data cleansing, survivorship rules, and exception handling. The incumbent will actively analyze, shape, and improve master data domains to ensure high data quality, trusted reporting, and scalable operational processes. In addition to leading cross-functional requirements and process improvement initiatives, this role will champion MDM and Data Governance practices by defining standards, resolving data quality issues at the source, and ensuring master data integrity throughout its full lifecycle. This role plays a critical part in enabling trusted, scalable data foundations that support enterprise analytics, reporting, and emerging AI-enabled business capabilities.

Requirements

5–7 years of experience in Business Analysis, Business Systems Analysis, or Data-focused roles with significant hands-on involvement in Master Data Management
Deep, practical expertise in MDM concepts, including: Taxonomy and hierarchy design, Entity and relationship modeling, Master and reference data connectivity across systems, Data cleansing, match/merge, survivorship, and exception handling
Demonstrated experience working directly with MDM platforms (e.g., Informatica MDM/Cloud, SAP MDG, Precisely, Reltio, or similar)
Strong understanding of core master data domains such as Customer, Product, Vendor, Location, or Asset
Hands-on data analysis skills (Excel, SQL basics, Power BI/Tableau) with the ability to diagnose and resolve data quality issues
Strong facilitation and communication skills with the ability to bridge business and technical audiences

Nice To Haves

Defining and operationalizing data stewardship roles, data quality rules, and remediation workflows
Exposure to data governance and metadata tools (e.g., Collibra, Alation, Atlan)
Exposure to modern data platforms (e.g., Snowflake) and understanding of how curated data supports analytics and AI workflows
Familiarity with data governance frameworks (e.g., DAMA-DMBOK, DCAM)
Experience working within Agile/SDLC environments using tools such as Jira or Azure DevOps

Responsibilities

Act as a hands-on MDM subject matter expert, deeply involved in the structure, behavior, and lifecycle of master data
Design and maintain taxonomies, hierarchies, attributes, and entity relationships across master data domains (e.g., Customer, Product, Vendor)
Understand and document how master data entities relate to each other across systems (MDM, ERP, CRM, data warehouse, downstream consumers)
Partner closely with IT and data engineering teams to implement and enhance MDM capabilities, including golden record creation, match/merge logic, survivorship rules, and source system connectivity
Proactively identify, analyze, and remediate data quality issues such as duplicates, missing attributes, invalid values, misaligned hierarchies, and broken relationships
Define and execute data cleansing and exception-handling processes, including root-cause analysis and prevention strategies
Map current-state (“as-is”) business and data processes, explicitly incorporating master data creation, maintenance, enrichment, and governance touchpoints
Design future-state (“to-be”) processes that improve data quality, usability, and operational efficiency
Embed data governance and MDM lifecycle controls into process designs to ensure sustainability
Lead discovery workshops and working sessions focused on MDM use cases, data flows, and system integrations
Translate business needs into detailed functional and data requirements, including entity models, attribute definitions, validation rules, and exception scenarios
Serve as a translator between business stakeholders and technical teams with a strong command of both business context and MDM technical concepts
Analyze master and transactional data to uncover quality issues, usage patterns, and improvement opportunities
Support operational and governance decisions through targeted analysis, dashboards, and reporting
Quantify the business impact of MDM and data quality improvements, including downstream effects on analytics, reporting, and decision-making
Define and maintain data standards, including naming conventions, definitions, and master/reference data boundaries to support a consistent, enterprise-wide source of truth
Maintain a business glossary and data definitions with particular emphasis on master data attributes and relationships
Support stewardship workflows, ownership models, and change control processes for master data
Ensure master data is structured and governed to support downstream analytics, reporting, advanced analytics and AI use cases