ABOUT US

At Displayr, our mission is to make it easier for everyone to find and share the stories in their data. We do this by creating software that makes it easy to do all aspects of data analysis and reporting, from simple tables through to machine learning, PowerPoint automation to online dashboards.
Our Engineering team is at the heart of this mission, and we need YOU.
As a bootstrapped company with no corporate debt or external advisors, we’ve grown steadily over seven years from 11 to over 100 team members, serving 1,700+ clients, including industry leaders like Nielsen, Meta, and Amazon. We’ve earned recognition as a Great Place to Work for two years in a row and ranked 1st in ANZ’s Best Tech Companies 2023.
We’re also proud partners with Work180, championing diversity, inclusion, and flexible working for women. Displayr won the Equitable Workplace Awards for flexible working in both 2023 and 2024.
With our head office in Sydney and teams across Australia, New Zealand, North America, and the UK, we’re shaping the future of data storytelling—join us as we make data more accessible, insightful, and actionable.

ABOUT THE ROLE

We’re looking for a Quality Engineering Team Lead to drive automation, improve engineering quality, and lead a team of talented engineers. This is a hands-on leadership role, where you’ll contribute to automation frameworks and infrastructure while setting technical direction and maintaining the highest quality standards. Since your team consists of Software Engineers, strong technical ability is essential—you need to be comfortable managing engineers, solving complex technical problems, and writing code yourself.

RESPONSIBILITIES:

• Lead & mentor a high-performing team of Quality Engineers.
• Be a subject matter expert in test automation, quality engineering, and release processes.
• Foster innovation and continuous learning within your team.
• Drive an automation-first culture, reducing manual testing efforts.
• Identify & remove blockers, ensuring smooth releases and high developer velocity.
• Define and track key quality engineering metrics (test coverage, automation effectiveness, defect rates, and release stability).
• Continuously improve test infrastructure, automation tools, and release workflows.