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Principal, Quality Eng; Data & Analytics

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: EBRD
Full Time position
Listed on 2026-10-31
Job specializations:
  • IT/Tech
    IT QA Tester / Automation
  • Quality Assurance - QA/QC
    IT QA Tester / Automation
Salary/Wage Range or Industry Benchmark: 110000 - 145000 GBP Yearly GBP 110000.00 145000.00 YEAR
Job Description & How to Apply Below

Requisition

Office Country United Kingdom

Office City London

Division Information Technology

Contract Type Regular

Contract Length

Posting End Date 03/11/2026

Principal, Data and Analytics Quality Engineering Lead

Shape how quality is engineered across mission-critical financial platforms.

This is a rare opportunity to lead Quality Engineering at scale, driving intelligent automation, embedding quality into every stage of delivery, and redefining how enterprise data, integration and analytics platforms are tested, validated and trusted. You’ll operate across a diverse technology landscape spanning Microsoft Fabric, EBX, Azure Integration Services, Informatica IDMC and Control‑M orchestration, bringing together modern QE practices, AI‑driven insights and deep domain expertise to ensure resilience, accuracy and performance where it matters most.

If you’re passionate about transforming quality from a checkpoint into a strategic engineering capability and want to make a visible impact in a complex, regulated environment, this is your moment.

What You’ll Do
  • Define and lead Quality Engineering strategy across the Data & Analytics platform estate, ensuring quality is embedded from design through to operational support across data, integration, master/reference data and reporting capabilities.
  • Lead platform-wide assurance across Microsoft Fabric, EBX, Azure Integration Services, Informatica IDMC and Control‑M, ensuring consistent quality standards, automation patterns and governance controls across the full technology landscape.
  • Embed automation‑first testing into CI/CD pipelines, covering functional, regression, reconciliation, interface, data quality and operational validation across cloud data platforms and integration services.
  • Define validation approaches for Microsoft Fabric workloads, including Lakehouse and Warehouse structures, Medallion Architecture flows, Data Factory pipelines, notebooks, semantic models, Power BI outputs and Direct Lake reporting patterns.
  • Establish QA practices for EBX master and reference data capabilities, including workflow validation, hierarchy testing, data governance rule validation, reference data integrity and integration with downstream consuming platforms.
  • Define assurance patterns for Azure Integration Services, including API and interface testing, message validation, event‑driven integration, retry handling, exception paths, monitoring, alerting and resilience scenarios.
  • Lead QA for Informatica IDMC and related data integration services, including ingestion, transformation, reconciliation, lineage validation, data quality rules and migration assurance from legacy platforms where applicable.
  • Shape testing for the target‑state Control‑M orchestration model, covering batch scheduling, dependency validation, restartability, recovery, SLA monitoring, operational handover and end‑to‑end runbook assurance.
  • Align QA practices with regulatory frameworks including SOX, DORA and IFRS, and modern delivery models including Agile, Dev Ops, Data Ops and QA‑Ops.
  • Partner with business domain experts, data owners, architects and engineering teams to ensure data accuracy, integrity, lineage, financial validation and operational resilience are built into test strategies.
  • Design test data and environment strategies for complex financial, integration and analytics scenarios, including payments, GL postings, month‑end processes, master/reference data updates, batch orchestration and downstream reporting.
  • Drive innovation in testing using AI/ML techniques, performance engineering, observability, service resilience validation and data quality analytics.
  • Elevate engineering maturity through shift‑left and shift‑right testing, reusable automation frameworks, quality gates, continuous improvement…
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