Senior QA Automation Engineer – Reporting & Analytics
Salary: €75,000 + bonus, pension, healthcare, and life cover
Role Overview
Join a dynamic data engineering team as a Senior QA Automation Engineer, driving quality and reliability across advanced data, API, and analytics platforms. You’ll lead automation initiatives, shape testing strategies, and ensure accuracy and performance across complex data ecosystems.
Key Responsibilities
Design, implement, and maintain automated testing frameworks for data pipelines, APIs, and analytics solutions.
Collaborate with engineers and analysts to define test approaches, acceptance criteria, and quality metrics.
Champion best practices for QA automation and influence testing strategies across teams.
Deploy and manage automation frameworks in the cloud.
Define and report on key quality and performance indicators.
Develop and execute functional, integration, regression, and performance tests.
Validate data integrity across batch and streaming datasets.
Test Spark-based pipelines (Databricks, Delta Lake, MLflow).
Verify Angular front‑end and .NET back‑end services.
Validate Power BI reports for accuracy and usability.
Integrate automated tests into CI/CD pipelines (Octopus, GitHub Actions, Azure DevOps).
Participate in peer reviews and maintain QA standards.
Support testing during development, UAT, and release cycles.
Document test outcomes and provide actionable insights.
Required Experience
Degree in Computer Science, IT, or equivalent practical experience.
5+ years in QA or software testing focused on data engineering or large‑scale systems.
Strong Python skills for automation and data validation.
Hands‑on experience testing Databricks (Spark, Delta Lake, MLflow) pipelines.
Advanced SQL for data reconciliation and transformation testing.
Testing experience with Angular and .NET applications.
Power BI testing expertise for analytics validation.
Experience with Azure or other major cloud platforms.
Familiarity with Git or similar version control tools.
Strong communication and teamwork skills.
Experience working in Agile (Scrum or Kanban) environments.
Desirable Skills
ISTQB certification or equivalent QA credential.
Experience with Azure Data Services (Data Factory, Data Lake Gen2, Databricks).
Proficiency with PyTest or similar test automation frameworks.
Familiarity with Infrastructure as Code (Terraform).
Understanding of data governance and quality frameworks.
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