Analyst, Big Data Analytics & Engineering
Mastercard
- Location
- Pune, India
- Work model
- On-Site
- Level
- Mid
- Posted
- Sep 7, 2026
Skills
About this role
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Analyst, Big Data Analytics & Engineering Overview: About Mastercard Mastercard is a global technology leader in the payments industry, committed to powering an inclusive, digital economy that benefits everyone, everywhere. By leveraging secure data, cutting-edge technology, and innovative solutions, we empower individuals, financial institutions, governments, and businesses to achieve their potential. Our culture is driven by our Decency Quotient (DQ), ensuring inclusivity, respect, and integrity guide everything we do. Operating across 210+ countries and territories, Mastercard is dedicated to building a sustainable world with priceless opportunities for all. ________________________________________ Position Overview Based in Gurgaon, India, this is a techno-functional position that combines strong technical skills with a deep understanding of business needs and requirements. The role focuses on developing and maintaining advanced business analytics and AI-driven solutions for pre-sales value quantification. As an Analyst, you will be responsible for creating and optimizing tools that help Mastercard’s internal teams quantify the value of services, enhance customer engagement, and drive business outcomes. You will combine AI and analytics to deliver actionable insights, empowering teams to make informed decisions and strengthen client value propositions. The role requires close collaboration across teams to ensure tools meet business needs and deliver measurable impact. ________________________________________ Role Responsibilities 1. Value Quantification & Tool Development Develop tools and solutions to quantify the value of Mastercard’s services during the pre-sales process, enabling internal teams to effectively communicate value to customers. 2. Data Analysis and Management Manage and analyse large datasets using SQL and other database management systems to support value quantification efforts. Perform statistical analysis to identify trends, correlations, and insights that inform strategic decisions 3. Business Intelligence and Reporting Utilize business intelligence platforms such as Tableau or Power BI to create insightful dashboards and reports that communicate the value of services Generate actionable insights from data to inform strategic decisions and provide clear, data-backed recommendations 3. AI & Analytics Integration for Business Impact Use AI and advanced analytics techniques to enhance pre-sales tools, enabling data-driven insights that support customer engagement, strategic decision-making, and business outcomes. 4. Cross-Functional Collaboration & Stakeholder Engagement Collaborate with Sales, Marketing, Consulting, Product, and other internal teams to understand business needs and ensure successful tool development and deployment. Communicate insights and tool value through compelling presentations and dashboards to senior leadership and internal teams, ensuring tool adoption and usage to senior leadership and internal teams, ensuring tool adoption and usage. 5. Insight Generation, Reporting & Process Optimization Generate actionable insights from data to inform strategic decisions, providing clear, data-backed recommendations to improve pre-sales efforts and customer engagement. ________________________________________ All About You Data Analytics and Business Intelligence: Proficiency in data analytics tools and techniques to analyse and interpret complex datasets.