QA Engineer

hace 2 semanas

Desde casa, México AppIQ Tech A tiempo completo

AppIQ Tech is seeking a meticulous and strategic QA Engineer / Sr. QA Engineer to ensure the quality and reliability of our Machine-Learning-driven e-commerce funnel optimisation and digital advertising platform.

As a key member of our fast-paced startup, you will balance the need for rapid feature deployment with the necessity of thorough testing. You will be responsible for identifying and prioritising the highest-risk bugs to ensure our scalable services, which manage millions of daily events, remain robust and accurate.
- **Risk Management**: Prioritise bug fixes based on risk of failure and potential impact, while striking a productive balance between speed-to-market and exhaustive testing.
- **Test Management**: Utilise test case management (TCM) systems such as TestRail, Zephyr, Xray, PractiTest, qTest, or similar to organise test cases, track execution, and provide transparent reporting on quality metrics.
- **Automated Testing**: Design, implement, and scale automated test suites using tools such as Playwright, Cypress, and Appium.
- **Infrastructure Testing**: Verify the reliability of deployments across AWS (EC2, S3, Firehose) and Cloudflare edge environments.
- **Data Integrity**: Collaborate with Data Engineers to validate the accuracy of complex event data and real-time reporting dashboards.
- **Cross-Functional Collaboration**: Act as a great team player with excellent communication skills, working closely with developers and data scientists to ensure a seamless end-user experience.

**Requirements**:

- Strong grasp of QA architecture and modern testing methodologies.
- Deep expertise in the tech stack used by our engineers, specifically TypeScript, React, Node.js, Python, and PySpark.
- Cloud & Database Proficiency: Familiarity with AWS services and both SQL and NoSQL (e.g., MongoDB) databases to effectively test data persistence and performance.
- Global Collaboration: Ability to work effectively with globally distributed teams.

**Strong plus if you also have**:

- AI/ML Literacy**: Understanding of Machine Learning (Supervised/Reinforcement Learning), Predictive AI, and the validation of Data Pipelines.
- Proficiency in Python or experience with PySpark.
- Prior experience in the e-commerce or Ad Tech ecosystem (DSPs, Audience Data, Fraud detection).

**Benefits**
- The opportunity to shape the QA culture and architecture from the ground up.
- An attractive career path on either a management or an individual contributor track.
- Genuine learning, training and development opportunities, supported by regular performance reviews
- Competitive compensation and generous paid time off.
- Work-from-anywhere flexibility

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