Lead QA Automation Engineer (Python)

LTM

$100K — $130K *
Media
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience as a QA Lead or Senior QA Engineer
  • Proficient in JavaScript and/or Python for API automation
  • Expertise in AWS services including S3, Lambda, and ECS
  • Hands-on experience with load testing tools like Locust
  • Strong analytical and mentoring skills across cross-functional teams

Responsibilities

  • Lead and mentor a team of QA engineers to enhance testing practices
  • Own the testing strategy for the entire data lifecycle including API exposure
  • Validate large-scale data using AWS tools ensuring accuracy of metadata
  • Design and maintain automation frameworks integrated into CI/CD pipelines
  • Execute high-scale load tests and analyze performance for optimal latency
  • Build dashboards and maintain documentation for test strategies and reports

Benefits

  • Opportunity to lead QA in a cutting-edge cloud media platform
  • 100% remote work flexibility
  • Collaborative environment with cross-functional leadership
  • Focus on AI innovations in QA processes
  • Access to advanced testing tools and methodologies
Full Job Description
Role description

Job Title: Lead QA Automation Engineer (Python)

Work Location: Mississauga ON

Work Mode: 100% Remote

Job Description
We are building a largescale cloud native media content platform that handles end-to-end data ingestion processing and consumption APIs for millions of media assets articles videos audio This system processes massive datasets 100GB and powers advanced keyword category and AIdriven semantic search capabilities

We are seeking a proactive QA Senior Lead to drive quality assurance across this entire ecosystem This role requires deep technical expertise in API testing data validation and automation architecture combined with the leadership skills to mentor a team implement shift left strategies and collaborate with cross functional leadership to deliver highly reliable distributed systems

Mandatory Responsibilities
QA Leadership Strategy Lead and mentor a team of QA engineers Define the overall QA strategy champion shift left practices in the SDLC and align quality goals with Product Engineering and DevOps stakeholders
End-to-end API Pipeline QA Own the testing strategy for the complete data lifecycle Ingestion Processing Storage API Exposure Validate push/pull ingestion workflows SNSSQS scheduled jobs and complex consumption endpoints keyword category and semantic search APIs
Large-Scale Data Validation Validate millions of JSON records using AWS S3 Athena SQL and Glue Crawlers Ensure the accuracy of metadata mappings date logic and licensable filtering across multiple publications
Automation Framework Architecture Design and maintain scalable automation frameworks using JavaScript Jest or Python Pytest Integrate API automation and JSON schema validation into CICD pipelines AWS CodeBuild with comprehensive reporting
Performance Load Testing Design and execute high-scale load tests using Locust Analyze system bottlenecks ALB ECS downstream services to ensure optimal API latency p95/p99 and semantic search throughput
Observability Documentation Build and monitor dashboards New Relic OpenSearch to track system health Create and maintain high-quality Confluence documentation for test strategies edge cases and performance reports
Optional Future Focused Responsibilities Nice-to-Have
AI Semantic Search System Validation Validate AIpowered features including embedding generation AWS Bedrock Cohere and vector based retrieval in OpenSearch
AIDriven QA Innovations Pioneer LLMbased automated test case generation and establish frameworks to validate semantic accuracy
Advanced Test Infrastructure Architect automated ephemeral test environments and implement contract testing or service virtualization
Container Streaming QA Test event-driven streaming systems and leverage knowledge of Docker and Kubernetes for test deployments
Advanced Database Validation Work with and validate complex data models in Vector and Graph databases

Required Skills Qualifications
Experience Proven track record as a QA Lead/Senior QA Engineer managing complex distributed systems and largescale ETLData pipelines
Automation Deep proficiency in JavaScript and/or Python for backend and API automation REST JSON validation
Cloud Infra Expertise in the AWS ecosystem S3 Lambda API Gateway ECS ALB SQSSNS Athena and OpenSearch Elasticsearch
Testing Tools Hands-on experience with load testing tools Locust and modern CICD pipelines
Soft Skills Strong analytical thinking excellent cross-functional communication and a proven ability to mentor teams and debug complex production issues in dynamic environments

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