QA Automation Engineer
New
C
Coherent SolutionsFinancial services
Location: Poland; Candidate Work Type: ['Remote']; Job Location: ['Poland'], Sometimes meetings are possible up to 8-9 pm (Poland time), not everyday but in general it's possible.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years of software QA experience; minimum 2 years of programming experience
- Required Skills
- SQLJavaJavascriptAirflowRESTful APIs
Requirements
- Have 4+ years of software QA experience, including work with web applications, REST APIs, and/or Salesforce.
- Have at least 2 years of programming experience, including Java; Spring Boot experience is preferred.
- Bring advanced SQL skills, including complex queries, data validation, reconciliation, and data profiling.
- Understand data architecture, including Medallion, and be familiar with Airflow, DAGs, data pipelines, and transformations.
- Be able to understand system architecture and infrastructure.
- Triage issues, adapt to changing priorities, and manage work across multiple products and projects.
- Collaborate across teams, facilitate constructive discussions, and help teams reach decisions.
- Mentor teammates, share knowledge, delegate work, and promote accountability.
- Establish QA practices, coding guidelines, tools, and processes, and introduce useful technologies where appropriate.
- Be available to occasionally join meetings scheduled as late as 8–9 p.m. Poland time.
- Experience with API testing tools such as RestAssured or Unirest is preferred.
- Experience with JavaScript UI automation frameworks such as Cypress, Playwright, or WebdriverIO, or iOS/Android automation frameworks, is preferred.
- Familiarity with TestRail or Jira, Datadog, and Google Cloud Platform is preferred.
Responsibilities
- Build and maintain automated API tests for services owned by the Data Engineering team.
- Write SQL checks to validate data quality and transformations.
- Test data pipelines and verify data across the different layers of the data architecture.
- Check the accuracy and consistency of data used in reports and investor-facing materials.
- Support end-to-end testing across Data Engineering services.
- Identify test coverage gaps and establish appropriate QA processes and standards.
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