Benefits:

Long Term

Onsite

Opportunity for advancement

Sr SDET – Data & Platform Quality Location: Dallas, TX Long Term

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