CO

SME-Product info & MDM

Cognizant Technology Solutions India Pvt Ltd
Chennai ₹5-9 LPA Posted 4 Nov 2026
FULL TIME
Data Modeling
Data Governance
product data management
Data Validation
trading systems

Job Description

Responsibilities

  • Own end-to-end product information and master data setup for order management and trading systems, ensuring accurate attribute codes and lifecycle status for every product record across all platforms.
  • Improve order management workflows by evaluating trading and fulfillment data, then proposing streamlined processes that reduce cycle times, enhance data reliability, and enable scalable retail operations.
  • Oversee daily night shift data processing jobs for product and order records to detect anomalies, conduct root cause analysis, and coordinate corrective actions to safeguard downstream systems and reporting.
  • Build and enforce robust data validation rules and quality checks for product and order master data to ensure consistency across hybrid work locations and compliance with internal governance standards.
  • Partner with technology and business teams to translate order management and trading requirements into well-defined data models, mappings, and rules for seamless execution and reporting.
  • Document master data procedures covering product onboarding, order lifecycle updates, and trading events to give operations teams clear guidance and support repeatable, high-quality data management.
  • Manage change requests for product information and master data, including updates to attribute hierarchy and code changes, to reduce business disruption and maintain a single trusted source of data.
  • Assess retail order patterns and data issues to recommend improvements that lower order exceptions, strengthen customer experience, and support the company mission of delivering reliable services to society.
  • Assist with integration testing for enhancements to order management and trading platforms by validating master data behavior and confirming that product and order flows perform correctly in night shift scenarios.
  • Deliver timely data insights and reporting on master data health, including key metrics and issue trends, to support informed decisions that improve operational efficiency and business performance.
  • Mentor peers on best practices in product information and master data management by sharing practical examples that reinforce data stewardship and responsible use of information assets.
  • Ensure day-to-day data activities align with company purpose by maintaining accurate product and order information that supports transparent trading, reliable supply chains, and improved outcomes for customers and communities.
  • Maintain compliance with internal policies and external regulations related to product and trading data by regularly reviewing data standards and updating practices as requirements evolve.

Qualifications

  • Bring strong hands-on experience in order management and trading systems, including configuration data handling and issue resolution, gained through four to seven years in comparable roles.
  • Apply practical knowledge of retail order processes and order management retail concepts to design master data setups that support promotions, returns, and complex fulfillment scenarios.
  • Use solid understanding of order domain concepts—including order capture, pricing, allocation, and settlement—to ensure that product information and master data structures support end-to-end process integrity.
  • Demonstrate proficiency with master data management tools, relational databases, or enterprise resource planning platforms to maintain large product catalogs and order-related reference data.
  • Communicate effectively with cross-functional stakeholders and document technical and process details in a structured manner to support hybrid work collaboration during night shifts.
  • Show analytical strength and strong attention to detail when working with complex trading and order datasets, using problem-solving techniques to prevent recurring data issues.
  • Demonstrate adaptability to hybrid work and night shift expectations through disciplined time management and self-organization, maintaining high data accuracy and service quality without travel commitments.
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