Senior MDM Product Data Analyst

This role is in-person in the Bangalore office. No remote work is possible.

THE ROLE

We are seeking an experienced MDM Product Data Analyst to support the management, quality,
governance, and transformation of product master data across enterprise systems. The role will work
closely with Product, Business, Engineering, Data Governance, and technical teams to analyze complex
product data, define and validate data quality rules, support MDM onboarding and migration, and drive
resolution of data issues. The ideal candidate combines strong product data and MDM expertise with
advanced SQL, analytical problem-solving, and practical use of AI/GenAI to improve data analysis and
delivery.

WHAT YOU'LL DO
• Analyze, manage, and reconcile product master data across multiple source systems, MDM platforms,
and downstream applications.
• Leverage AI/GenAI tools to accelerate data profiling, analysis, data quality rule development,
documentation, issue investigation, and root-cause analysis.
• Translate business and product requirements into clear data requirements, attribute definitions,
validation rules, and analytical specifications.
• Perform detailed data profiling to identify quality issues, gaps, inconsistencies, anomalies, duplicates,
and data integrity risks across product attributes and relationships.
• Define, document, implement, and validate data quality rules covering completeness, accuracy,
validity, consistency, uniqueness, and business-rule compliance.
• Develop source-to-target analysis and reconciliation approaches to validate data movement,
mappings, transformations, and synchronization across systems.
• Work with Product and Business stakeholders to understand product structures, SKUs,
product/component relationships, configurations, classifications, and product lifecycle requirements.
• Analyze and resolve complex product data issues, including incorrect attribute values, missing data,
duplicate records, mapping issues, hierarchy discrepancies, and configuration gaps.
• Support MDM data onboarding, enrichment, cleansing, migration, and transformation activities,
including data preparation and validation.
• Develop data validation logic and partner with technical teams on implementation, testing, and
automation of DQ rules.
• Participate in UAT, data certification, defect triage, root-cause analysis, and issue resolution; ensure
defects are clearly documented and tracked through closure.
• Create data correction files and coordinate with technical teams to implement and validate required
fixes.
• Support development and maintenance of product data dictionaries, attribute definitions, business
rules, reference data, and data governance documentation.
• Partner with Data Governance teams to define data ownership, standards, allowed values, reference
data, and validation requirements.
• Monitor and report data quality metrics, trends, defects, and remediation progress, providing clear
status updates and recommendations to stakeholders.
• Identify recurring data quality issues and recommend process, data model, integration, or system
improvements to prevent recurrence.
• Contribute to large-scale MDM implementation, migration, and transformation programs and support
continuous improvement of product data processes.

WHAT YOU BRING

• 8+ years of relevant experience in Data Analytics, Master Data Management, Product Data
Management, and/or Data Quality.

• Hands-on experience working with Reltio as an MDM platform.
• Strong hands-on experience working with Product Master Data and Product Catalog data.
• Strong understanding of SKU structures, product hierarchies, attributes, product/component
relationships, configurations, lifecycle, and classification.
• Strong SQL skills for data extraction, profiling, reconciliation, validation, and investigative analysis.

• Hands-on experience with data quality frameworks, DQ rule development, data profiling, and issue
remediation.
• Experience performing source-to-target data analysis, reconciliation, mapping validation, and
integration analysis.
• Strong understanding of data governance concepts including data ownership, data standards,
business rules, reference data, and allowed values.
• Experience with CPQ, Product Catalog, Salesforce, Zuora, NetSuite, or CRM systems.
• Experience working with hardware, software, SaaS, or subscription-based product data.
• Experience with product configuration and product/component relationships.
• Experience working with Snowflake.
• Familiarity with automated data quality tools such as Ataccama.
• Practical experience using AI/GenAI tools to improve data analysis, DQ rule development,
documentation, and root-cause analysis.
• Experience supporting UAT, data certification, defect triage, and cross-functional issue resolution.
• Experience supporting large-scale MDM implementation, migration, or transformation programs.
• Strong analytical, structured problem-solving, and attention-to-detail skills.
• Excellent written and verbal communication skills, with the ability to present data findings, risks, and
recommendations to both technical and business stakeholders.
• Ability to work effectively across Product, Engineering, Data Governance, Business, and technical
teams.
• Experience analyzing complex product catalogs with high volumes of SKUs and attribute
combinations.
• Experience developing reusable data validation and reconciliation approaches for recurring data
quality checks.
• Experience identifying opportunities to automate manual data analysis, validation, and remediation
activities using AI/GenAI or scripting.
• Understanding of enterprise product data integrations and downstream consumption patterns.
• Experience working in Agile delivery environments and participating in requirements grooming,
backlog refinement, and data-focused delivery planning.

Key Competencies
• Product Data & MDM expertise
• Data Quality & Governance
• SQL & Data Analysis
• Source-to-Target Reconciliation
• Product Structures, SKUs & Configurations
• AI/GenAI-enabled Data Analysis
• Problem Solving & Root-Cause Analysis
• Stakeholder Management & Communication

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