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Salary
≈ $74k – $145k per year (Estimated)
Location
In office (London)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Sep 18, 2026.

Overview
Company
Impact
Profile match
DataArt is a global software engineering and consulting firm headquartered in New York that builds and modernises custom software, data platforms and cloud infrastructure for clients in finance, travel, healthcare, media and retail. Founded in 1997, it runs delivery centres across Europe, the Americas and Asia, including offices in Wroclaw, Lublin and Lodz in Poland and teams in India, and works with more than 400 enterprise clients. Its openings include senior .NET, Java, Python and frontend engineers, DevOps and site reliability engineers, data architects and data engineers, QA automation leads and solution consultants.

This is a data focused quality engineering role rather than an application testing role. You will build automated validation for data pipelines and data products, own reconciliation testing between legacy and target systems, and put quality gates into the delivery pipeline so that a failure blocks a release rather than producing a report that nobody reads.

Location: UK remote, including remote London.

The project migrates data and reporting from a legacy estate onto a modern platform built on Databricks and Microsoft Fabric. Quality engineering is central to the project. The business needs confidence that migrated data reconciles with the source, that pipelines behave as specified, and that reports produce consistent results.

  • 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.
  • 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 at a level suitable for direct client conversations.
  • Experience with Microsoft Fabric.
  • Experience with Sapiens.
  • Experience with data quality frameworks, including Great Expectations, dbt tests, Databricks Expectations, DLT quality rules, Soda, or Deequ.
  • Experience designing a test framework from scratch rather than extending an existing one.
  • Experience testing semantic models and BI layers.
  • Experience working in a regulated financial services environment.
  • Experience with application test automation alongside data testing, including Selenium, C#, SpecFlow, or Playwright.
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