QA Lead Engineer

Natural Intelligence is a global leader in the online comparison market. Our goal is to simplify decision-making and connect customers with valuable brands.

Our technology helps millions of consumers around the world make smarter, more confident buying decisions. We do so by creating trusted comparison websites that enable consumers to easily compare products and services online and form high-value relationships with the brands they choose. Our partner brands, some of which are among the most prominent websites worldwide, utilize our platform to maximize their online presence. 

We are looking for a passionate, highly motivated Software Quality Engineer to lead the QA process in our R&D Group. As a QA Lead, you’ll play a key role in the development life cycles, which will include product specification analysis, risk management, guiding the R&D team, and doing hands-on automatic and manual QA testing.


 Responsibilities:

  • Lead the end-to-end quality lifecycle from product specification to production monitoring. 
  • Use/Build automation tools to validate all users’ funnels, data integrity, system performance, and alert on broken flows.
  • Create dashboards to provide transparency on production state, use tools to identify issues, bugs, and errors, and lead investigations to deliver feedback.
  • Work closely with product, operation, business colleagues, and development team.
  • Inspire developers, designers, and product owners to be quality conscious by providing extensive training and workshops about testing culture and best practices.
  • Use data to learn about our user behavior, patterns, most/least used features, etc., and make data-driven decisions.

Requirements

  • At least 5 years experience in testing web systems
  • At least 2-3 years experience with automation (developing automation infrastructure and designing test plans)
  • Skill and drive to develop automation tools and streamline the overall testing process
  • Demonstrated creative and analytical problem solving and decision-making skills
  • SQL knowledge
  • Experience with monitoring and log anomaly detection tools - an advantage
  • Experience using JavaScript or TypeScript - an advantage

 

*Only suitable CVs will be considered

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QA Lead Engineer