#22331_R-276725
ndustry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our culture is guided by the Mastercard Way-own it, simplify it, sense of urgency, thoughtful risk taking, unlock potential, and be inclusive.
Job Summary:
We are looking for a highly skilled Senior QA Engineer / SDET with deep expertise in testing large scale batch and real time data platforms built on Apache Spark, Kafka, and Apache NiFi.
This role focuses on validating streaming heavy architectures, ensuring data correctness, latency, fault tolerance, and reliability across complex distributed systems leveraging object storage platforms such as Apache Ozone and Ceph.
The ideal candidate is passionate about data quality, test automation, observability, and production readiness for mission critical big data systems.
Analyze business, regulatory, and technical requirements to design risk based and audit compliant test scenarios.
Develop, maintain, and execute test plans, test cases, and test data with appropriate documentation and traceability to requirements.
Perform functional, regression, and system integration testing in accordance with enterprise quality standards and release controls.
Log, track, and manage defects in JIRA, ensuring clear reproduction steps, impact assessment, and lifecycle traceability.
Validate JSON payloads, cloud storage data, and Apache NiFi data flows to ensure data accuracy, completeness, and integrity.
Collaborate with development teams to support timely defect resolution and adherence to quality gates.
Participate in design reviews, test plan reviews, and technical documentation
Participate in Agile ceremonies, providing clear and accurate test execution status, risk assessments, and quality metrics.
Test Kafka based streaming pipelines, including topic partitioning, offsets, throughput, and ordering guarantees
Verify event replay and reprocessing flows using Kafka offsets and Spark checkpoints
Test Apache NiFi flows for ingestion, routing, back pressure handling, error paths, and retry semantics
Execute performance, load, and soak testing for Spark batch and streaming workloads
Collaborate with engineering teams to validate partitioning strategies, resource tuning, and scalability assumptions
Build and maintain test automation frameworks for data validation, streaming verification, and regression testing
Automate validation using SQL, PySpark, and Python based test harnesses
Integrate automated tests into CI/CD pipelines for data applications
Participate in production validation, go live readiness, and post deployment verification
Support incident analysis through data validation, replay testing, and root cause analysis
Validate observability metrics such as lag, throughput, latency, error rates, and data drift
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: