Software Development Engineer in Test developing automated test frameworks and ensuring software quality for vehicle systems. Collaborating closely with developers in a dynamic QA team.
About the role
- Senior SDET owning automation quality for large-scale data-heavy platforms using Python in a hybrid work setup. Responsibilities include building automation frameworks and validating data systems.
Responsibilities
- Design, build, and maintain Python-based test automation frameworks, not just individual test cases
- Define reusable test libraries for validating data platforms and distributed systems
- Drive automation standards, patterns, and best practices across teams
- Validate Kafka-based event streams, including:
- ◦ Topic-level data validation
- ◦ Producer and consumer behavior
- ◦ Message schemas, payload integrity, ordering, and replay scenarios
- ◦ Failure handling, retries, and dead-letter scenarios
- Test asynchronous workflows and event propagation across services
- Validate end-to-end data flows across distributed services and pipelines
- Test backend APIs, service integrations, and asynchronous processing layers
- Perform schema validation, transformation checks, data consistency, and completeness validation
- Test cloud-native data platforms built on AWS services such as:
- ◦ S3, Glue, Redshift, Lambda (or similar services)
- Validate ingestion, processing, storage, and downstream consumption of data
- Debug data and automation failures across multiple cloud services
- Embed automation into CI/CD pipelines
- Enforce quality gates and fail pipelines on critical data or platform issues
- Provide actionable feedback to engineering teams based on automation results
- Work closely with data engineers, platform engineers, and architects
- Define test strategies for event-driven and distributed data systems
- Proactively identify quality risks and gaps in platform design
Requirements
- Strong test automation engineering experience using Python
- Hands-on Kafka testing experience (real production systems, not theoretical knowledge)
- Proven experience testing distributed and event-driven systems
- Solid understanding of data validation concepts, including:
- ◦ Schemas and contracts
- ◦ Transformations and enrichment
- ◦ Data consistency, completeness, and accuracy
- Experience working in AWS-based data platforms
- Ability to debug and troubleshoot issues across multiple services, not just log defects
- Engineering mindset with ownership mentality
- Nice to Have
- Experience with schema registries (Avro / JSON / Protobuf)
- Knowledge of streaming vs batch data architectures
- Familiarity with observability, logging, and monitoring in distributed systems
- Experience working in high-volume, near-real-time data environments
Benefits
- Competitive compensation
- Hybrid Opportunity for advancement
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