The QA Engineer will own end-to-end test strategy across distributed data integration services, ensuring quality across APIs, Kafka event pipelines, and downstream data systems.
The role requires strong expertise in manual and automation testing, with deep understanding of data validation across multi-stage pipelines.
Key Responsibilities
- Design layered test strategy covering unit, integration, contract, and system testing for data-driven platforms
- Perform AVRO schema validation and contract testing using Schema Registry (forward/backward compatibility)
- Test Kafka-based event pipelines including producers, consumers, and end-to-end data flow validation
- Build and maintain automated test suites using PyTest / Jest / Selenium / equivalent frameworks
- Validate data across API → Kafka → database → warehouse layers (e.g., DynamoDB / Snowflake)
- Coordinate UAT with business stakeholders, including defect triage and release sign-offs
- Execute integration and API testing using mock/sandbox environments
- Perform idempotency and data consistency testing across distributed systems
Required Skills
- 5+ years in QA / SDET / Test Automation roles
- Strong experience in API testing and automation frameworks (PyTest / Selenium / Jest / similar)
- Hands-on experience with Kafka event-driven systems
- Strong understanding of data validation and ETL testing concepts
- Experience in integration testing of microservices or distributed systems
- CI/CD exposure (Jenkins / GitLab / GitHub Actions)
Good to Have
- AVRO / Schema Registry experience
- Kafka tooling (kafka-console-consumer, Confluent tools)
- Performance / soak testing experience
- Experience with idempotency testing and data consistency validation
- Exposure to cloud data systems (Snowflake / BigQuery / Redshift)