Product Owner - 2 Enterprise Data

• 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 new 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.

Requirements

• 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.

Benefits

• 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.
• Career growth with pathways into senior product leadership, domain specialization, or cross-functional roles.