Job Description
About the Role
We're looking for an experienced Test Automation Engineer to join our team on a contract basis to support the build-out of our automated test framework and validation suite. You'll play a key role in designing, implementing, and maintaining automated functional, integration, performance, and acceptance tests across a modern data and cloud environment.
Key Responsibilities
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Design and implement automated test frameworks using Pytest for functional and regression testing.
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Develop and execute unit, integration, and API tests within the Pytest framework.
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Implement BDD (Behaviour-Driven Development) testing using Behave and Gherkin, defining clear, business-readable acceptance criteria.
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Develop and manage performance and load testing suites using Locust, with potential exploration of JMeter as an alternative.
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Write and execute SQL queries to validate data integrity across different layers (ODS/PDU).
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Integrate test automation with AWS services such as:
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Athena for data validation queries
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CloudWatch for logging test results and monitoring trends
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EventBridge for triggering automated test runs
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IAM Policy Simulator for access control and encryption/decryption testing
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Contribute to continuous integration and delivery pipelines by embedding automated testing practices.
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Explore and assess Great Expectations (GE) as a complementary or alternative data validation framework.
Skills & Experience Required
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Strong experience with Python for automation and Scripting.
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Proven track record implementing frameworks with Pytest (unit, integration, API, and regression testing).
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Hands-on experience with BDD frameworks such as Behave and Gherkin.
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Knowledge of performance testing tools such as Locust (and ideally exposure to JMeter).
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Proficient in SQL for data validation and testing.
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Familiarity with AWS services, particularly Athena, CloudWatch, EventBridge, S3, and IAM.
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Understanding of CI/CD pipelines and test automation integration.
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Strong analytical mindset and attention to detail.
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Excellent communication skills and ability to work collaboratively within cross-functional teams.
Nice to Have
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Experience using Great Expectations (GE) for data quality validation.
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Exposure to data-driven testing and cloud-based data architectures.
