Company 90 percent of everything is transported by sea. At 90 POE, we help ship owners and operators take care of the other percentages that matter. We understand that many of the factors influencing this industry can’t be controlled. Overall demand, oil prices and the weather are out of your hands. But you can control how you respond to them.
5 января 2021

Data QA Engineer

Киев, удаленно

Необходимые навыки

• 3+ years of experience in Software development as Automation QA / SDET
• Strong prooved experience building complex e2e solutions from scratch
• Ability to analyze and troubleshoot complex data-based testing scenarios
• Familiarity with cloud-based / micro-services architecture

More about you
• Good level of English
• Willingness to learn and open mind about new technologies
• Confident to operate in a fast-paced environment
• A collaborative approach and willingness to engage in an environment of active idea sharing
• Ability to learn autonomously
• Excellent all-round communications skills

Будет плюсом

• Experience with any messaging system
• k8s experience
• SDET experience desirable

Предлагаем

• We offer a competitive financial package which includes competitive salary and quarterly bonus scheme
• We have a positive attitude to flexible working, a competitive annual holiday allowance, cycle to work scheme and supportive family polices
• State of the art, cool, centrally located offices with warm atmosphere, which creates good
working conditions
• Opportunity to travel to client offices based in London
• We have a culture of which we are proud, a highly skilled and diverse workforce as well as impressive offices in central London and Kiev

Обязанности

What you will be responsible for
Primarily we are looking for somebody to manage from design to execution the testing phase related to all time-series streaming data pipelines:
• Define acceptance criteria
• Prepare test data
• Designing and develop tests, mocks and stubs
• CI/CD pipeline building
• Test results analysis
This is a hands-on position for an expert QA engineer. In addition to practical coding and QA skills, an important aspect is played by soft skills tasks such as:
• Researching, gathering, organizing tests around data
• Evangelizing the importance of testing with real-world data to strength the system
• Enhancing a cultural shift in intensive data applications development cycle

О проекте

Ninety Percent of Everything is looking for an experienced professional to join the team on a full-time basis, as Data QA Engineer.
Our goal is to revolutionise shipping by creating a suite of comprehensive software solutions for the Maritime industry. Our journey begins now. Over the next couple of years, our teams and squads will build more than 30 products from the ground up. This includes everything from global vessel tracking to vessel performance analysis, crew optimisation and so much more. This is an exciting and challenging opportunity to apply cutting-edge technology to revolutionising an iconic industry.

Our tech stack consists of React, React Native and Flutter applications communicating using GraphQL to microservice containers orchestrated by Kubernetes. Most of our services is written in Golang with stream processing in Java, they use gRPC for communication, achieve high scalability thanks to Apache Kafka based event driven architecture, persist data to a mix of RDBS and No-SQL databases including PostgresDB, MongoDB, Cassandra, S3 and Elasticsearch. We follow CI/CD and agile methodologies to deploy into production multiple times per week.

The Role
90POE’s mission is big. It is not going to be easy but with the support and determination from our stakeholders and the brilliant people we have hired we can achieve anything. Right now, we are seeking an experienced Data QA engineer to validate our data stream pipelines. Raw Data is streamed in our system by processes like ETL, after aggregation, enrichment and manipulation results are saved into materialized views that product teams rely on to build user applications. 90poe is looking to improve the capability of testing such data pipeline.
We expect that the right candidate would acquire maritime domain specific knowledge, thanks to the high exposure to domain data, therefore no prior domain expertise is required.

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