Position: QA Engineer, Data Pipelines
Company: DataRobot
Experience required: 2y
English level: intermediate

**Job Summary**
DataRobot changes the way users build, deploy and monitor highly accurate machine learning models. What does it take to develop the highest quality data science product on the market?  A hybrid testing strategy that combines humans and automation and gets the best of both worlds.

Our QA Philosophy at DataRobot is one of Quality “Assistance” rather than assurance; as a result, our lean team focuses on empowering every engineering team to own the quality of their code and ensure adequate test coverage for new features.

In addition, the Quality team works on world-class data science and data engineering testing applications that stretch the boundaries of the code and implement performance engineering practices.

At DataRobot, QA engineers work together with the development and product team to ensure customer satisfaction in terms of functionality, usability and performance. 

In the Data Pipelines team at DataRobot, you will work on pipeline technologies that handle terabytes of data with speed, interactivity, correctness checks and monitoring. This requires an innovative and can-do mindset to tackle some of the most difficult challenges of ensuring quality for complex distributed compute in Spark. Don’t be daunted — we are willing to help you learn and develop your skills and career here at DataRobot!

**Responsibility**
As a QA engineer, you will:

Test new features for upcoming releases and review technical specs for new features.
Help writing test plans, test reports and provide suggestions in improving the QA processes.
Write and execute exploratory tests for new features.
Communicate with product and development teams to develop a strong understanding of the product requirements, technical execution plan, and testing objectives.
Review test coverage of new features and provide suggestions to improve their quality.
Use third-party automated tools for adding and maintaining regression tests.
Review results of automated tests and analyze failures and performance regressions
Analyze new feature performance against established baselines.
Be an active member of the team, suggesting improvements of the processes to increase quality of the product and performance of the team.
Ability to stay updated with features built by other teams, identify its impacts, and test feature interactions.

**Required experience: **

3+ years of professional quality assurance and testing experience with web applications.
Experience with Python scripting
Working knowledge of setup and troubleshooting of Docker/Kubernetes.
Good knowledge of testing theory, especially of exploratory testing methods.
Experience with REST API testing.
Experience with test management tools, (TestRail), automation servers (Jenkins), version control software (GitHub, Bitbucket), and Linux and/or Mac OS X.
Working knowledge of AWS technologies like Amazon EC2 servers, and S3 storage.
Ability to understand technical specifications.
English proficiency -- both verbal and written communication. 
Desired experience:

Experience in Bash and JavaScript 
Experience working with Cypress for browser-based testing  (Selenium or similar is also valuable). 
Experience with gRPC communication patterns
Participation in PR reviews.
Experience with performance and resiliency testing.
Experience with IDE and managing code.
Experience with pytest and test runtime optimization.