Overview This organisation builds cloud-based technology platforms that simplify complex operations and improve day-to-day experiences for large institutions and their users.
By combining data, analytics, and modern software engineering, the company delivers reliable, insight-driven solutions at scale.
Responsibilities Design and evolve automated testing frameworks covering data pipelines, APIs, analytics platforms, and applications Own quality practices for data platforms, influencing standards and improving testing approaches across teams Validate data correctness, consistency, and performance across batch and streaming workloads Test large-scale Spark-based pipelines, including transformation logic and outputs Work closely with product, engineering, and analytics teams to define test strategies and acceptance criteria Verify front-end applications and backend services built on modern web and cloud technologies Ensure reporting and dashboards deliver accurate, reliable insights Embed automated testing into CI/CD pipelines and cloud deployments Track and report quality KPIs, contributing to continuous improvement Support testing across development, UAT, and post-release phases, providing clear, actionable feedback Skills & Experience Strong background in QA automation within data teams Several years' experience testing data-intensive platforms or distributed systems Proficiency in Python for test automation and data validation Advanced SQL skills for reconciliation, transformation, and performance checks Hands-on testing experience with big data technologies and cloud platforms (Azure preferred)Comfortable working in Agile environments (Scrum / Kanban)Experience with source control and modern Dev Ops workflows Confident communicator with strong written and verbal English Nice to Have Experience with Databricks, Spark, Delta Lake, streaming data, or similar technologies Familiarity with Power BI or analytics/report testing Exposure to CI/CD tools, infrastructure automation, or cloud-native deployments
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