Data Analyst

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 Data Analyst Overview • Are you excited about Data Assets and the value they brings to an organization? • Are you an evangelist for data driven decision making? • Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across 6 continents? • Do you want to be the go-to resource for data analytics in the company? Role • Design, develop, and maintain scalable ETL/ELT pipelines supporting enterprise data and analytics initiatives. • Build and optimize batch and real-time data processing solutions using SQL, Python, Spark, and related technologies. • Ensure data availability, accuracy, consistency, and reliability across data platforms and pipelines. • Implement data quality controls, testing frameworks, monitoring, and observability practices to support trusted data products. • Apply engineering best practices including version control, CI/CD, DataOps, and automated deployment methodologies. • Support platform upgrades, migrations, operational maintenance, and ongoing production support activities. • Collaborate with Data Engineers, Data Scientists, Analysts, and business stakeholders to translate business requirements into scalable data solutions. • Participate in technical design reviews, code reviews, and architecture discussions to drive engineering excellence. • Create and maintain technical documentation, standards, and operational procedures. All About You • Hands-on experience in data engineering, data integration, and large-scale data processing. • Strong proficiency in SQL and Python for data transformation, automation, and analytics workloads. • Solid understanding of data modeling, database design, and performance optimization techniques. • Experience designing and developing ETL/ELT solutions across modern data platforms. • Knowledge of data quality frameworks, testing methodologies, and data validation practices. • Familiarity with cloud-based or modern enterprise data platforms. • Experience with source control, CI/CD pipelines, and software engineering best practices. • Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues. • Excellent communication and collaboration skills with the ability to work effectively across technical and business teams. • Self-motivated, detail-oriented, and committed to delivering high-quality, scalable solutions. Preferred Qualifications • Experience with PySpark and Apache Spark for distributed data processing. • Experience working within the Hadoop ecosystem and large-scale data environments. • Familiarity with GitLab, Jenkins, or similar DevOps and CI/CD platforms. • Exposure to Power BI or other business intelligence and data visualization tools. • Understanding of modern data architecture patterns supporting analytics, machine learning, and AI workloads. Education • Bachelor’s or Master’s Degree in a Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S./M.B.A. preferred Additional Competencies • Excellent English, quantitative, technical, and communication (oral/written) skills • Analytical/Problem Solving • Strong attention to detail and quality • Creativity/Innovation • Self-motivated, Self Starter, operates with a sense of urgency • Project Management/Risk Mitigation • Able to prioritize and perform multiple tasks simultaneously