Sr SDET Data Platform Quality

Benefits

• Competitive compensation
• Hybrid work model
• Opportunity for advancement

We are seeking a Senior SDET to own automation quality for large-scale, data-heavy, event-driven platforms. This role focuses on backend, Kafka, and AWS data platform validation using Python-based automation frameworks.

This is a hands‑on engineering role, not a traditional QA position.

• No manual testing
• No UI / Selenium‑only testing
• No basic ETL script validation

• 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

• 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

• 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

• Location:
  
  Dallas, TX (Hybrid — 3 days per week in‑office)
• Interview Process:
  In‑Person Interview
• Locals & Non‑Locals Can apply.
• Flexible work from home options available.