Munna Kumar

Enterprise Data Quality & MDM Analyst with 5 years of experience in Master Data Management, Data Stewardship, and Data Governance. Hands-on expertise in Reltio MDM data enrichment, match & merge, and golden record creation. Proficient in Power BI, Collibra governance workflows, and SQL-based data reconciliation with 99% accuracy. Experienced in developing dashboards, supporting business decision-making through accurate and reliable enterprise data.

Data Quality Analyst - Allegis group - Hyderabad

(2025-05 - 2026-05)

• Performed end-to-end Reltio MDM operations — data enrichment from external sources, match & merge with 80% threshold scoring — creating single golden records for customer and store master data.
• Managed customer and store master data in Salesforce — ensuring 99%+ accuracy and consistency across enterprise systems.
• Handled 200+ daily data requests within SLA — validating and updating store addresses, contact numbers, and store names using multi-source cross-verification.
• Self-learned Power Automate and automated 2–3 repetitive manual workflows — reducing processing time from hours to minutes.
• Designed and published Power BI Service dashboards using semantic data models, tracking data quality KPIs including intake volume, completion rate, duplicate rate, error trends, and aging analysis.
• Improved overall data quality by 45–48% through SQL systematic validation, standardization, and enrichment of critical master records.
• Used Collibra data governance platform — covering metadata harvesting, business glossary, data quality rules, data classification, and data lineage
• Collaborated with logistics and business stakeholders to resolve data quality issues and support operational reporting.

Senior Associate - Genpact India - Hyderabad

(2024-01 - 2025-03)

• Managed end-to-end supply chain master data across Asian countries — processing 20,000–30,000 monthly records across customer, product, asset, and operational datasets.
• Wrote and executed advanced SQL queries including window functions, aggregate functions, and multi-table joins — to extract, validate, and reconcile data across SQL Server and Oracle databases for cross-system master data verification.
• Performed cross-system data reconciliation across 3–4 CRM platforms validating GTIN numbers, part numbers, and serial numbers to ensure 99% data accuracy across full manufacturing to maintenance lifecycle.
• Managed parent-child asset hierarchies in medical device part numbers as parent records, component serial numbers as child records ensuring correct mapping for complete asset lifecycle tracking.
• Processed enterprise data creation requests within 24–48 hour SLA locating and validating records across 5 source systems via GTIN and part numbers and creating master records in globally standardized format in Reltio.
• Built 3 Power BI dashboards and operational trackers monitoring backlog, request volumes, aging analysis, data quality trends, and KPI performance across enterprise supply chain teams.
• Enforced enterprise data governance policies — ensuring master data accuracy, standardization, and compliance across supply chain and medical device datasets with zero unauthorized updates.

MIS Executive Analytics - Allied Digital - Hyderabad

(2022-04 - 2023-09)

• Extracted and analyzed IT operations data from ticketing tools to generate daily, weekly, and monthly reports for operational performance tracking and service management reporting.
• Built and maintained Power BI dashboards and KPI reports to monitor SLA compliance, ticket volumes, backlog trends, resolution timelines, and operational performance, improving issue resolution efficiency by 15%.
• Maintained 99%+ accuracy in ITSM reporting by performing data validation, reconciliation, and deduplication across incident and service request.

Doc Auditor - NSB BPO - Noida

(2020-10 - 2022-01)

• Performed real-time data validation and verification of 300+ daily customer records within strict SLA matching and cross-verifying identity data across multiple data points to ensure compliance before approval.
• Identified and resolved data discrepancies to improve overall data quality and reduce approval errors.
• Followed defined data standards and validation processes — completing each case within 5 minute SLA to maintain reliable, accurate, and compliant customer records.

B.A. - History & Psychology - Jay Prakash University (2013 - 2018)