Position: Senior Manual QA Engineer
Company: GlobalLogic
Category: QA
Experience required: 3y
English level: upper

Job Description
BS in Computer Science, Engineering, Mathematics or related field

QA/testing experience of Big Data environments (microservices, Docker, ETL, Spark, Kubernetes, AWS, etc.) is a plus

Knowledgeable of security requirements

Strong verbal and written communication skills; demonstrated influencing skills, high level of technical and team leadership skills

Tendency to automate and monitor everything, preferably in Python or Java

Strong aptitude for troubleshooting/problem-solving

Self-motivated and comfortable working in an Agile methodology (rapid iterations, rapid releases, etc)


Job Responsibilities
Work as part of a scrum team, and closely with the back end developers, to groom stories and create and execute test plans

Manually test completed stories to ensure that as a team, we are delivering a high quality product

Perform manual integration and load tests as appropriate to prevent regressions

Automate testing as time allows

Ensure SLA requirements are continuously improved through technology innovation and end-to-end monitoring and support capabilities

Leverage, and contribute to, the testing automation infrastructure


Department/Project Description
We are looking for an outstanding Senior Manual QA Engineer to play a key role in developing an industry-leading storage analytics solution. The platform collects and analyzes more sensor data points from our customers’ infrastructure systems and applications than there are stars in our galaxy. Predictive Analytics is then used to correlate vast amounts of information to find the needle in the haystack, and solve our customers’ most complex infrastructure issues.

You will be joining an agile, empowered team, focused on building a brand new data processing platform. The platform provides abstractions, components, and infrastructure to create a state-of-the-art platform for running data processing and machine learning workloads. The team leverages the latest big data and microservice-based technologies to build out the data processing platform – Apache Spark, Delta Lake, Apache Pulsar, Kubernetes, Istio, knative, GraphQL, TimescaleDB, Postgres. The development stack is Scala (cats, http4s, Caliban, shapeless, lagom).


Keyskills - Must Have
Manual functional testing QA