Quality Assurance Lead Engineer

At Continuum, you have an opportunity to change how data scientists and analysts use technology to make discoveries that solve the world's greatest challenges. You will be part of a growing company whose products connect the brightest minds with their data, while learning a great deal both from those you work with and the customers you support. Our team is innovative, passionate, fun and hardworking. We are looking someone who wants to work out of our awesome office in downtown Austin, Texas.

The Role:

The Quality Assurance (QA) Lead is responsible for ensuring the quality and robustness of our software, and also responsible for designing the processes that ensure that quality.  They will formalize test strategies, design and coordinate the build-out of our internal automated test infrastructure, drive our outsourced manual testing team (via that team’s project manager), and work extensively with the product team Dev Leads as well as the Product Managers.  The candidate must have great communication skills, an ability to coordinate and drive complex projects, and sharp problem-solving skills.  A familiarity with data analysis or data science software is a nice-to-have, but not a hard requirement.

Main Responsibilities:

  • Develop detailed test plans and real-world test scenarios based on high-level workflows from Product Management
  • Develop automated and manual test infrastructure, and support Ops/DevOps as they maintain it
  • Serve as primary point of contact for the engineering aspects of QA for the rest of the company, including Sales Engineering, Support, and Product Management.

Desired Background:

  • Creative and agile problem solver, with strong attention to detail, but able to “zoom out” and see the broader problem landscape
  • Good communicator, both in person and via email and chat.
  • Basic knowledge of software testing approaches and best practices
  • Experience with test automation tools and configuring them
  • Knowledge of data analysis & data science workflow patterns is not a pre-requisite, but a strong “nice to have” for this position.

Help Us Shape the Future of Data

Continuum is seeking people who want to play a role in shaping the future of data, analytics, and visualization. Candidates for technical roles should be knowledgeable and capable, but always eager to learn more and to teach others. Overall, we strive to create a culture that is both relaxed and focused, and we stress empathy and collaboration with our customers, open source users, and with each other.  Our primary employee perk is that we are actively working on things that have a global impact, whether it's modeling risk and detecting fraud in the financial markets, or accelerating cancer research or fighting human trafficking and terrorism.

We are part of a global community on the cutting edge of open source analytics, and our employees gain exposure and participate in all that.

Continuum Analytics develops Anaconda, the leading open data science platform powered by Python. More than two million users have adopted the Anaconda platform in less than three years, and growth continues to accelerate. Customers include more than 200 of the Fortune 500, 19 of the Fortune 25 and 8,000 universities around the world. Boeing, Procter & Gamble, Pepsi, Schlumberger, the U.S. Department of the Treasury and the Securities and Exchange Commission are among current industry leaders who rely on Anaconda.

To learn more about the Anaconda platform, training and consulting services, visit www.continuum.io.

 


Meet Some of Continuum Analytics's Employees

Duane L.

Director Of Sales Engineering & Implementation

Duane and his team provide potential customers with sales insights, putting together presentations to explain how Continuum Analytics' products can help solve their problems.

Kristopher O.

Software Engineer

Kristopher works to develop both products and software for Continuum Analytics. In addition to creating code, Kristopher acts a Continuum consultant on projects in financial and scientific computing sectors.


Back to top