Sr SDET Data & Platform Quality

Job Description Benefits:Competitive compensationHybridOpportunity for advancementSr SDET Data & Platform QualityLocation: Dallas, TX (Hybrid 3 days per week in-office)Interview Process: In-Person InterviewLocals & Non-Locals Can apply.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 testingNo 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 teamsKafka & 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 resultsCollaboration & 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 architecturesFamiliarity with observability, logging, and monitoring in distributed systemsExperience working in high-volume, near-real-time data environmentsFlexible work from home options available.