Senior System Analyst
Who is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
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.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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**Corporate Security Responsibility**
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
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