Analyst, Big Data Analytics & Engineering

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 Background Mastercard is on a journey to modernize and advance our Finance Technology landscape, covering Billing, Financial Planning, Accounting, Settlement, Treasury, Reporting and Analytics. This position will be responsible for developing and delivering high-impact technology solutions that align with our business and technical objectives. By collaborating with cross-functional teams, including business/product owners and other technical experts, you will ensure that our solutions meet evolving customer needs while improving performance, scalability, and reliability. Responsibilities - Partnering with data owners, engineering and platform teams to establish robust data pipelines, implement data models, and ensure seamless integration across diverse systems and domains. - Ensure alignment between business goals and technical execution, making sure features and solutions meet business requirements and customer needs. - Participate in sprint planning, retrospectives, and other agile ceremonies to ensure the team is aligned and delivering efficiently. - Adoption of best practices in software / data engineering, including automated code reviews, testing, and continuous integration/continuous delivery (CI/CD). - Optimize the cost/benefit of software features and architecture, ensuring scalability, performance, and operational efficiency. - Ensuring solutions align with Mastercard’s engineering and data principles, and technical policies. - Identify opportunities for process improvements, helping to streamline workflows and enhance team productivity. - Work closely with Product Owners / business to understand requirements and implement technical solutions with engineering best practices. - Stay abreast of Data Platform technology trends and industry best practices to hone and maintain your talent - Participate in architectural discussions, iteration planning, and feature sizing meetings - Adhere to Agile processes and participate actively in agile ceremonies All About You -8+ years of hands-on experience developing solutions on Cloud data platform, including Databricks. Proven experience as a data engineer, with a strong focus on delivering large-scale projects in an agile environment. -Hands-on experience in Databricks and deep understanding of its architecture. Design, develop and implement large-scale, high-volume, high-performance, highly available, scalable data-based solution and pipelines for the Databricks Lakehouse platform in AWS cloud -Hands-on experience developing and supporting data lakes, lakehouses, warehouse on-premise and on cloud, ETL solutions and other analytics solutions. - Prior experience with financial systems, such as Oracle Financials, Oracle Fusion Cloud, and Hyperion, with experience optimizing their integration into broader data ecosystems, is a plus. - Experience with data lifecycle management, including ingestion, ETL, pruning, modeling, and governance, within highly regulated environments. - Expertise in modern data engineering best practices, CI/CD, automated testing, and code reviews, etc. - Experience in partnering with data owners and other engineering and platform teams to build and manage a single source of truth for data, leveraging end-to-end technology stacks and best practices in data architecture. - Strong programming skills in Python and frameworks, with a focus on building scalable, reliable, and performant s ... (truncated, view full listing at source)