COCognizant Technology Solutions India Pvt Ltd
SME-Product info & MDM
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.
