\\\\Our Purpose\\\\ \Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, were 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\\\\ Software Engineer II OVERVIEW: Mastercard is the global technology company behind the world's fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. As a Data Quality Engineer in Data Platform & Engineering Services, you will have the opportunity to build high performance data pipelines to load into Mastercard Data Warehouse. Our Data Warehouse provides analytical capabilities to number of business users who help different customer provide answer to business problems through data. You will play a vital role within a rapidly growing organization, while working closely with experienced and driven engineers to solve challenging problems. Key Responsibilities: Build and enhance data quality validation frameworks for largescale financial and cardprocessing systems. Design, implement, and maintain automated data quality pipelines using Python, Spark, and SQL. Develop and integrate APIs that support data validation workflows, metadata services, and quality scoring. Build realtime streaming data quality checks using Kafka/Spark Streaming for highvelocity transaction data. Implement automated rules to validate data completeness, accuracy, timeliness, lineage, and business logic. Collaborate with platform, product, and analytics teams to ensure endtoend data reliability. Contribute to CI/CD, monitoring, alerting, and observability for data quality systems. Required Qualifications: Bachelors or Masters degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related technical field. Software engineering experience building data services or pipelines, with strong proficiency in Python (frameworks, packaging, testing, CI). Handson experience with Apache Spark (batch and/or streaming) for highvolume processing, including performance tuning and job orchestration. Advanced SQL skills for implementing validation logic and reconciliations in code (CTEs, windowing, partitioning), with a focus on query performance and reliability. Experience designing and consuming RESTful APIs for data quality services (rules management, metrics, metadata) and integrating them into applications/pipelines. Practical expertise with streaming platforms (Kafka, Kinesis, or Spark Structured Streaming) to enforce realtime data quality checks and SLAs. Handson with AWS (S3, Lambda, Glue, EMR, Step Functions, ECS/EKS, CloudWatch) and modern data lake/warehouse patterns; infrastructureascode experience is a plus (CDK/Terraform). Deep understanding of data quality dimensions (accuracy, completeness, timeliness, consistency, validity) and the ability to translate business rules into automated validation code and tests. Strong engineering practices: unit/integration testing, observability (logs/metrics/traces), performance optimization, secure coding, and CI/CD pipelines (GitHub Actions/Jenkins). Excellent problemsolving and communication skills; proven ability to collaborate with platform, product, and data teams in an agile environment. Preferred / Good to Have Exposure to AI/ML for anomaly detection, rule inference, or synthetic data generation to enhance automated DQ. Background in payments/card services (authorization, clearing, settlement) and related data models. Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable\\ and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. \\\\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 Mastercards 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 Mastercards guidelines. In line with Mastercards total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. \\\\Pay Ranges\\\\ O'Fallon, Missouri: $92,000 - $147,000 USD

A Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related technical field is required. The role necessitates software engineering experience in building data services or pipelines, with strong proficiency in Python, including frameworks, packaging, testing, and CI. Hands-on experience with Apache Spark for high-volume processing, including performance tuning and job orchestration, is essential. Advanced SQL skills for implementing validation logic and reconciliations are also required, with a focus on query performance and reliability. Experience designing and consuming RESTful APIs for data quality services and integrating them into applications/pipelines is necessary. Practical expertise with streaming platforms like Kafka or Spark Structured Streaming for real-time data quality checks and SLAs is also a requirement.