Sr SDET Data & Platform Quality

Select Minds

Dallas, Texas

JOB DETAILS
SKILLS
AWS Lambda, Agile Programming Methodologies, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Apache Avro, Application Programming Interface (API), Architectural Services, Automation, Automation Engineering, Backend as a Service (BaaS), Best Practices, Cloud Computing, Communication Skills, Consulting, Continuous Deployment/Delivery, Continuous Integration, Data Management, Data Quality, Database Extract Transform and Load (ETL), Debugging Skills, Distributed Computing, Engineering, Identify Issues, JSON, Philosophy, Production Systems, Profit & Loss, Python Programming/Scripting Language, Realtime Operating System, Risk Analysis, Scripting (Scripting Languages), Selenium, Software Design for Test (SDET), Software Testing, Team Player, Test Automation, Test Case, Test Strategy, Testing, User Interface/Experience (UI/UX), Validation Testing, Wheel/Front-End Loader
LOCATION
Dallas, Texas
POSTED
30+ days ago
Benefits:
  • Competitive compensation
  • Hybrid
  • Opportunity for advancement
Sr SDET – Data & Platform Quality
Location: Dallas, TX (Hybrid – 3 days per week in-office)
Interview Process: In-Person Interview
Locals & 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 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

Flexible work from home options available.

Compensation: $55.00 - $60.00 per hour




About the Company

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Select Minds