Sr SDET – Data & Platform Quality
Location: Dallas, TX (Hybrid – 3 days per week in-office)

Role Overview
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

You will design and own automation frameworks that validate Kafka-driven architectures, backend services, and cloud-native data pipelines, while partnering closely with data and platform engineers.

Key Responsibilities
Automation & Framework Ownership
• 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
 
Kafka & Event-Driven Systems Testing
• 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

Data Platform & Backend Validation
• 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

AWS & Cloud Data Testing
• 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

CI/CD & Quality Gates
• 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
 
Collaboration & Strategy
• 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

Required Experience (Non-Negotiable)
• 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