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 Analytics Engineer Overview• Responsible for defining and maintaining the data architecture and associated data maintenance, integration and load processes for the organization Responsibilities• Identifies and selects appropriate technologies, develops, builds, maintains and tests database technologies, including associated software products• Supports the development of SQL tuning statement procedures to optimize SQL tuning and query development• Assists in performing database implementations to ensure configuration, process, and procedure standards are in place• Supports database security posture which includes escalating potential concerns, and implementing both risk mitigation plans and control functions• Drafts and reviews status reports and performs implementation and troubleshooting activities• Provides high-level technical assistance to development programmers and customers to ensure proper database performances• Implements business and process improvements, formulating recommendations to increase database performance efficiencies• May manage smaller project/initiatives as an experienced individual contributor with specialized knowledge within assigned discipline Experiences• Experience in at least one database technology, technical or application area• Experience designing and testing database architecture standards or frameworks• Gains exposure to automation and/or cloud delivery effort• Experience participating in an assigned global technology domain or sub-domain (e.g., providing inputs around specific technologies)• Participates in business resource groups and global communities• Experience in AWS and Databricks• Python, Spark and Lakehouse knowledge 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: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

• Build experiences our customers love. Embed in the Video product org alongside PMs, designers, and engineers, using data to help shape and ship features athletes and their families actually use. You are a builder on the product team, not a reporting function next to it. • Strengthen and grow the data foundation. Make the models and pipelines we already have cleaner, more reliable, and more reusable, bring in new product, customer, and third-party signal we don't have today, and apply software discipline (version control, review, testing) throughout, so the team can trust the data and answer questions it currently can't. • Build experimentation into a system that scales. Stand up the data and analysis layer behind A/B tests so the team can design, run, and read experiments quickly and consistently, rather than rebuilding the plumbing each time. • Get instrumentation right at the source. Partner with product and engineering on event tracking and data contracts so the behavior we care about is captured accurately and completely from the start, then build the tests and monitoring that keep it that way. • Power product with live data APIs. Build and own data endpoints that feed real product experiences, from spec through production. • Surface insights and drive decisions. Turn the metrics that matter into clear, reliable insights and recommendations that move the business - building the dashboards and surfaces people trust to make decisions along the way. • Develop predictive and causal models. Develop predictive and causal models that move the business, from a pLTV model for revenue forecasting to a propensity model that targets discounts without cannibalizing revenue to causal-inference work that pinpoints which behaviors actually drive retention.

• Architect production-grade, fault-tolerant batch and real-time data pipelines within a compliance-governed AWS environment. • Lead data modeling (dimensional, SCD, data vault) and build API/file-based integrations with encryption and audit logging at every point. • Build CI/CD pipelines for data infrastructure with mandatory security scanning and approval gates. • Conduct code reviews, mentor engineers, and produce technical documentation including ADRs, runbooks, and compliance evidence packages.

• Build backend services, APIs, internal tools, lightweight UI/admin screens, automation, job runners, integrations, and customer-specific configuration around the data • Ingest, validate, transform, and document ERP, API, SQL, file, and cloud data; map product-defined KPIs to available sources and identify gaps or inconsistencies • Create validated, analysis-ready datasets with consistent schemas, reproducible transformations, and clear naming for reporting, APIs, product features, and customer-facing analytics • Deploy and operate reliable cloud solutions, preferably AWS, owning monitoring, alerts, failure handling, performance, cost, and operational reliability