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    Job · 12482148

    Mastercard logo

    Senior System Analyst

    Mastercard · Pune · onsite · Posted 63d ago

    Undisclosed8–10 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    Senior System Analyst






    Role Overview
    The System Analyst for the Workplace Intelligence Platform plays a critical role in bridging business needs with scalable technical solutions. This role focuses on translating complex workplace, sustainability, and enterprise data requirements into well-architected, high-impact analytics and platform capabilities. The analyst partners closely with business leaders, product teams, and engineering to drive data-driven decision-making and platform innovation.

    Key Responsibilities
    1. Technical Expertise & Solutioning
    Align product capabilities with enterprise technology strategies and evolving data platform architectures
    Contribute to scalable, modular, and reusable technical designs leveraging shared services and capabilities
    Translate business needs into detailed system requirements, data models, and technical specifications
    Develop prototype designs and recommend optimal solutions balancing feasibility, performance, and time-to-market
    Maintain deep expertise in a focused set of Workplace Intelligence products and use cases

    2. Requirements & Analysis
    Lead requirements gathering with business stakeholders to uncover underlying needs and define clear objectives
    Independently drive research and documentation for complex features and initiatives
    Structure large-scale requirements across multiple data domains (e.g., workplace, sustainability, finance)
    Identify synergies and conflicts across use cases and propose holistic solutions

    3. Data Strategy & Architecture
    Apply strong understanding of enterprise data strategy, governance, and data usage principles
    Recommend optimal data structuring approaches (e.g., entity design, transformations, historical tracking)
    Partner with engineering teams on data modeling decisions across data lake, warehouse, and API layers
    Ensure data quality, integrity, and compliance across solutions

    4. Problem Solving & Insight Generation
    Break down complex problems using structured, hypothesis-driven approaches
    Perform detailed analysis and generate actionable insights with high accuracy
    Validate outputs rigorously and refine solutions based on findings
    Proactively investigate inconsistencies and drive deeper analysis where needed

    5. Planning, Prioritization & Execution
    Lead feature planning, scoping, and estimation in collaboration with product and engineering teams
    Create clear execution plans across the full feature lifecycle (requirements development release)
    Prioritize high-impact work, adapt to changing needs, and proactively mitigate risks
    Coordinate dependencies across teams, vendors, and stakeholders

    6. Stakeholder Management & Communication
    Communicate complex technical concepts clearly to both technical and non-technical audiences
    Tailor messaging based on audience and drive alignment across diverse stakeholder groups
    Proactively share progress, risks, and next steps to ensure transparency
    Facilitate discussions and build consensus across teams

    7. Product Ownership & Advocacy
    Contribute to product roadmap, backlog prioritization, and long-term platform vision
    Advocate for usability, adoption, and continuous improvement of platform features
    Monitor feature performance, usage, and feedback to drive enhancements
    Ensure strong alignment with business use cases and end-user needs

    8. Testing, Support & Continuous Improvement
    Define test scenarios, validate outputs, and review results to ensure quality delivery
    Troubleshoot complex issues, identify root causes, and implement sustainable fixes
    Enhance documentation, usability, and monitoring based on support insights
    Drive continuous improvement in team processes and delivery practices

    9. Team Collaboration & Mentorship
    Act as a strong thought partner across product, engineering, and analytics teams
    Mentor junior analysts and promote best practices in analysis and design
    Foster collaboration, knowledge sharing, and a culture of innovation

    Key Skills & Qualifications
    Strong experience in system analysis, data platforms, or analytics solutions
    Deep understanding of data architectures (data lake, warehouse, APIs, medallion architecture)
    Proficiency in SQL and familiarity with modern data technologies (e.g., Iceberg, Hadoop/Ozone, cloud platforms)
    Excellent problem-solving, analytical, and structured thinking skills
    Strong communication and stakeholder management abilities
    Experience working in Agile/SAFe environments

    What Success Looks Like
    High-quality, scalable solutions aligned with business and technology strategy
    Clear, structured requirements enabling efficient delivery
    Strong stakeholder trust and effective cross-team collaboration
    Continuous improvement in platform capabilities, usability, and adoption






    Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

    Sourced from naukri

    Skills

    data qualityAgileSystem analysisProduct EngineeringContinuous improvementPrototypeAnalyticsSQLanalyticalData Modeling

    About MasterCard

    Mastercard logo

    Mastercard

    FinTech

    7.9k+

    employees

    1966

    60 years old

    Purchase,New York

    United States

    About

    Payments Technology company enabling transactions

    Industries

    FinTechFinancial ServicesInternet

    Employee ratings

    1,001 reviews

    3.8/ 5

    Culture

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    Career growth

    3.1

    Work-life

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