Software Engineer II
About The Position
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.
Requirements
- Bachelor’s or Master’s 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).
- Hands‑on experience with Apache Spark (batch and/or streaming) for high‑volume 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 real‑time data quality checks and SLAs.
- Hands‑on with AWS (S3, Lambda, Glue, EMR, Step Functions, ECS/EKS, CloudWatch) and modern data lake/warehouse patterns; infrastructure‑as-code 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 problem‑solving and communication skills; proven ability to collaborate with platform, product, and data teams in an agile environment.
Nice To Haves
- 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.
Responsibilities
- Build and enhance data quality validation frameworks for large‑scale financial and card‑processing 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 real‑time streaming data quality checks using Kafka/Spark Streaming for high‑velocity transaction data.
- Implement automated rules to validate data completeness, accuracy, timeliness, lineage, and business logic.
- Collaborate with platform, product, and analytics teams to ensure end‑to-end data reliability.
- Contribute to CI/CD, monitoring, alerting, and observability for data quality systems.
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
