Design and implement comprehensive test plans for validating a modern Data Warehouse, ensuring it outperforms the legacy environment in terms of efficiency, reliability, and accuracy.
Identify and recommend appropriate testing tools aligned with the project's technology stack and performance goals.
Define and execute a Production Parallel Testing strategy to compare new and existing systems side-by-side for consistency and performance benchmarking.
Ensure validation of all business rules across complex datasets, including transformation logic and mappings.
Introduce and leverage AI-driven techniques or tools to enhance testing efficiency and data insights where applicable.
Required Skills
Strong experience validating large and complex datasets, ensuring the accuracy of data mapping, transformation logic, and end-to-end integrity.
Flexible and tool-agnostic mindset, with a willingness to adopt the best-suited tools for the project's specific needs.
Excellent analytical skills with the ability to interpret complex data flows, transformations, and dependencies.
Strong domain knowledge, preferably in large-scale transportation data systems.
Ability to identify gaps in current testing processes, propose improvements, and validate both source and target systems.
Familiarity with industry standards for safety, uptime, and system reliability in critical data environments.
Preferred Skills
Experience designing and scaling automated test frameworks for cloud-native or distributed data architectures.
Proficiency with API testing tools such as Postman or RestAssured.
Strong working knowledge of SQL, Python, and other scripting tools for ETL automation and data validation