Data analyst

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.

• 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.
• 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.

• 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.
• Bachelor’s or Master’s Degree in a Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S./M.B.A. preferred
• 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
• Будет плюсом: 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

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