Описание
DataArt delivers a data migration and reporting project that moves a legacy estate onto a modern platform built on Databricks and Microsoft Fabric. The project focuses on reliable data reconciliation, pipeline quality, and consistent reporting results.
Задачи
•Design and implement data testing and quality assurance frameworks
•Build automated validation for data pipelines and data products
•Own source-to-target reconciliation between legacy systems and the new platform
•Build repeatable regression packs that run unattended
•Write unit tests that execute automatically within CI/CD, with quality gates that can block a release
•Detect and handle schema drift and unexpected structural changes
•Validate reports, dashboards, and semantic models, including measure definitions, filter behaviour, and totals
•Apply AI-assisted techniques to test generation and coverage analysis, with human review
Требования
•5+ years of experience in quality engineering, with meaningful recent experience testing data or ETL processes rather than applications
•Strong Python and SQL skills used for building test automation rather than only running it
•Experience with pipeline validation, including row counts, control totals, referential integrity, and business rule assertions
•Experience with source-to-target reconciliation using defined tolerances
•Experience with test automation within CI/CD, including gates that block a release
•Experience with Azure Databricks
•Experience with Azure DevOps
•Experience with SQL Server
•English proficiency suitable for direct client conversations
Nice to have: Microsoft Fabric, Sapiens, data quality frameworks including Great Expectations, dbt tests, Databricks Expectations, DLT quality rules, Soda, or Deequ, designing a test framework from scratch, testing semantic models and BI layers, working in a regulated financial services environment, application test automation alongside data testing including Selenium, C#, SpecFlow, or Playwright.
Условия
UK remote, including remote London.
