Senior Analyst - Marketing

Mastercard
Pune, IndiaPosted 6 May 2026

Job Description

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 Senior Analyst - Marketing 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 Title Sr. Analyst, Marketing Analytics Role Summary This role involves supporting B2B Marketing Operations by building reliable, scalable data pipelines and decision-ready reporting systems. The candidate will own end-to-end funnel and attribution measurement across key marketing platforms, translating complex campaign and lifecycle data into clear metrics and insights. S(he) will deliver production-grade Power BI / Tableau dashboards, ensure data quality through testing and governance, and partner with stakeholders to drive adoption and performance. About you • Experience working with /or an understanding of Marketing Operations data in a B2B environment, supporting demand generation OR pipeline management of OR revenue attribution use cases. • Proven project level experience in data engineering and visualization platforms – MS Fabric / Databricks and MS Power BI / Tableau. • Strong understanding of common B2B marketing data sources, such as: Marketing automation platforms (e.g., Salesforce Marketing Cloud / Marketo, Eloqua / HubSpot / Pardot), CRM systems (e.g., Salesforce), Paid media and digital channels (LinkedIn, Google, programmatic platforms), and Web and campaign performance data. Salesforce CRM experience highly preferred. • Ability to understand and analyze end‑to‑end funnel metrics, including leads, MQLs, SQLs, pipelines, revenue, and conversion rates. • Experience working with campaign hierarchies, attribution models, and lifecycle stages, and translating them into reliable, explainable metrics. What you will deliver • Data Engineering & Pipeline Development Analyze and understand existing raw data sources (structured and semi‑structured) across multiple IMC systems. Design and build robust, scalable data pipelines using Microsoft Fabric / Databricks, and related tooling. Demonstrable understanding of the automation workflows in the Power Automate space and ability to design and build workflows to deliver automation projects. Create and manage a centralized data lake in Microsoft Fabric, following best practices for performance, security, and scalability. Implement data transformations, validations, and quality checks to ensure accuracy, consistency, and trust. Partner with upstream system owners to improve data reliability and usability. • Dashboard Design & Development Design and build high‑quality Power BI dashboards that are intuitive, visually compelling, and decision‑oriented. Apply strong UX and data visualization principles (clarity, hierarchy, consistency, accessibility). Translate complex data into clear narratives and insights tailored to different stakeholder audiences. Develop dashboards that are robust, scalable, and production‑ready, not one‑off analyses. • Tes ... (truncated, view full listing at source)
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