Key Responsibilities
• Business Analysis & Requirements Management
• Elicit, analyze, document, and validate business requirements.
• Translate business needs into clear, actionable product requirements.
• Perform impact analysis for proposed product, process, and data changes.
• Ensure requirements are complete, accurate, and aligned with business objectives.
• Support user acceptance testing and solution validation activities.
• Partner with stakeholders to identify opportunities for process and data improvements.
• Data Analysis & Research
• Conduct detailed analysis of enterprise data domains and datasets
• Investigate data quality issues, operational challenges, and business impacts.
• Perform root cause analysis and provide recommendations for resolution.
• Conduct data profiling, data mapping, data modelling, validation, and business rule analysis.
• Analyze external providers datasets to assess quality, coverage, and business applicability.
• Research industry trends, external data sources, and emerging capabilities relevant to MCO's enterprise data strategy.
• Perform comparative analysis of data providers, enrichment opportunities, and potential data solutions.
• Enterprise Data Management
• Support initiatives related to:
• Master Data Management (MDM)
• Reference Data Management
• Data Governance
• Data Quality Management
• Data De-Duplication
• Data Retention & Lifecycle Management
• Assist in defining business rules, matching logic, validation criteria, and governance processes.
• Support onboarding, evaluation, and integration of recent data sources.
• Contribute to the development of data standards and stewardship practices.
• Work closely with Architecture and Engineering teams to understand enterprise data models, data flows, and integration requirements.
• External Data Provider Collaboration
• Work with external data providers to understand data structures, quality, coverage, and business applicability.




• Assist in resolving provider-related issues and enhancement requests.
• Conduct research and analysis to support strategic data decisions.
• Maintain awareness of provider capabilities, roadmap changes, and industry trends.
• Product Ownership & Delivery
• Own, manage, and prioritize the Enterprise Data product backlog.
• Define clear user stories, acceptance criteria, business requirements, and functional specifications.
• Lead backlog refinement and participate in Agile ceremonies, including sprint planning, reviews, and retrospectives.
• Partner with Engineering and QA teams throughout the product development lifecycle to support release planning, testing, and validation.
• Make informed trade-off decisions balancing business value, technical feasibility, delivery timelines, and risk.
• Monitor product performance and identify opportunities for improvement after release.
• Stakeholder Management
• Partner with Product Managers, Product Owners, Engineers, Architects, Operations teams, and Business stakeholders.
• Communicate requirements, findings, recommendations, risks, and dependencies effectively.
• Build strong working relationships across cross-functional teams.
• Support discovery, roadmap planning, and prioritization activities.
• Facilitate discussions to ensure alignment between business requirements and solution design.
• Continuous Improvement
• Identify opportunities to improve product processes, data quality, and operational efficiency.
• Contribute ideas for enhancing Enterprise Data capabilities and services.
• Stay informed on industry trends,



data management practices, and emerging technologies.
• Promote a culture of continuous learning and improvement. Qualifications & Experience
• Required Qualifications
• Bachelor's degree in Business, Information Systems, Computer Science, Finance, Data Management, or a related field.
• 8+ years of experience as a Product Owner, Business Analyst, Data Analyst, Data Product Analyst, or similar role.
• Experience working with enterprise data products, master data, reference data, or shared data services.
• Strong business analysis and requirements management skills.
• Experience working with complex datasets, data models, data mappings, data flows, and integration requirements.
• Experience within Compliance, RegTech, Financial Services, Capital Markets, Risk Management, or related industries.
• Experience working with external data providers such as S&P; Global, FactSet, LSEG/Refinitiv, Bloomberg, Dun & Bradstreet, Moody's, or similar organizations.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Strong knowledge of Agile product delivery methodologies.
• Experience with SQL, data analysis tools, data modeling concepts, and Agile product development environments.
• Experience working with CI/CD, DevOps, and Behavior-Driven Development (BDD) methodologies.
• Preferred: Familiarity with the AI product lifecycle, prompt engineering concepts, and ethical AI considerations.
• Opportunity to work on global products used by leading financial institutions.
• Exposure to complex problem-solving across compliance, workflows, data, and automation.
• A collaborative culture that values innovation, ownership, and continuous learning.
• Competitive compensation and benefits aligned with the India market.
• Growth opportunities with pathways into senior product leadership, domain specialization, or cross-functional roles.

📌 Product Owner (India)
🏢 MCO
📍 India