Principal, Quality Eng; Data & Analytics

Experteer Overview In this role you will lead Quality Engineering across critical Data & Analytics platforms, embedding QA into design and delivery at scale. You will shape a strategic QE capability in a regulated financial environment, aligning across data, integration, and reporting to ensure accuracy, resilience and performance. You’ll drive AI-powered testing, automation-first approaches, and cross-functional collaboration to elevate testing as a core engineering discipline. This is a chance to impact how financial systems are validated and trusted at scale. Pay / Benefits * Define and drive the QE strategy for the Data & Analytics platform estate, ensuring quality from design to operations * Lead platform-wide QA across Microsoft Fabric, EBX, Azure Integration Services, Informatica IDMC and Control-M with consistent standards and governance * Embed automation-first testing into CI/CD pipelines for functional, regression, data quality and operational validation * Define validation approaches for Microsoft Fabric workloads (Lakehouse, Warehouse, Medallion Architecture, Data Factory pipelines, notebooks, semantic models, Power BI) * Establish QA practices for EBX master/reference data, including workflow validation, hierarchy testing and data governance rule validation * Define QA patterns for Azure Integration Services (API testing, message validation, monitoring, resilience) * Lead QA for Informatica IDMC data integration services including lineage and data quality rules * Shape testing for Control-M orchestration (batch scheduling, dependencies, recovery, SLA monitoring) * Align QA with SOX, DORA, IFRS and modern delivery (Agile, DevOps, DataOps, QA-Ops) * Partner with domain experts and engineers to ensure data accuracy, lineage and financial validation in test strategies * Design test data and environments for complex financial and reporting scenarios * Drive AI/ML-enabled testing, performance engineering, observability and data quality analytics * Advance engineering maturity with shift-left/right, reusable automation, and measurable QE outcomes Tasks * Demonstrable experience leading QA/Quality Engineering across modern Data & Analytics platforms (ingestion, transformation, orchestration, modeling, reporting, operational support) * Strong experience testing data platform configurations across Microsoft Fabric, Medallion Architecture, Azure Data Lake Gen2, SQL-based warehouses * Hands-on understanding of Microsoft Fabric workloads (Lakehouse/Warehouse, Data Factory, Dataflows Gen2, notebooks, Power BI, DAX, XMLA validation) * Experience validating end-to-end data flows across source systems, integration layers and downstream reporting * Experience or strong knowledge of EBX, Azure Integration Services, Informatica IDMC and Control-M-style scheduling/orchestration * Proficiency in writing/reviewing validation queries using T-SQL, Python, Power Query, DAX or equivalent * Experience embedding testing into CI/CD via Azure DevOps, Git workflows, quality gates and automated deployment controls * Strong leadership in QE or QA within enterprise/financial services/regulatory environments * Ability to define test, automation, environment and test data strategies for complex multi-platform delivery * Deep knowledge of test automation, data reconciliation, interface validation, regression, performance and resilience testing * Understanding of regulatory and operational risk considerations (SOX, DORA, IFRS, auditability, traceability, business continuity) * Ability to influence stakeholders and translate technical risk into business-facing insight * Excellent communication and strategic thinking for cross-functional alignment Key requirements *

core approaches for Microsoft Fabric workloads (Lakehouse, Warehouse, Medallion Architecture, Data Factory pipelines, notebooks, semantic models, Power BI) * Establish QA practices for EBX master/reference data, including workflow validation, hierarchy testing and data governance rule validation * Define QA patterns for Azure Integration Services (API testing, message validation, monitoring, resilience) * Lead QA for Informatica IDMC data integration services including lineage and data quality rules * Shape testing for Control-M orchestration (batch scheduling, dependencies, recovery, SLA monitoring) * Align QA with SOX, DORA, IFRS and modern delivery (Agile, DevOps, DataOps, QA-Ops) * Partner with domain experts and engineers to ensure data accuracy, lineage and financial validation in test strategies * Design test data and environments for complex financial and reporting scenarios * Drive AI/ML-enabled testing, performance engineering, observability and data quality analytics * Advance aa Microsoft maturity with shift-left/right, reusable automation, and measurable QE outcomes Tasks * Demonstrable experience leading QA/Quality Engineering across modern Data & Analytics platforms (ingestion, transformation, orchestration, modeling, reporting, operational support) * Strong experience testing data platform configurations across Microsoft Fabric, Medallion Architecture, Azure Data Lake Gen2, SQL-based warehouses * Hands-on understanding of Microsoft Fabric workloads (Lakehouse/Warehouse, Data Factory, Dataflows Gen2, notebooks, Power BI, DAX, XMLA validation) * Experience validating end-to-end data flows across source systems, integration layers and downstream reporting * Experience or strong knowledge of EBX, Azure Integration Services, Informatica IDMC and Control-M-style scheduling/orchestration * Proficiency in writing/reviewing validation queries using T-SQL, Python, Power Query, DAX or equivalent * Experience embedding testing into CI/CD via Azure DevOps, Git workflows, aaa test gates and automated deployment controls * Strong leadership in QE or QA within enterprise/financial services/regulatory environments * Ability to define test, automation, environment and test data strategies for complex multi-platform delivery * Deep knowledge of test automation, data reconciliation, interface validation, regression, performance and resilience testing * Understanding of regulatory and operational risk considerations (SOX, DORA, IFRS, auditability, traceability, business continuity) * Ability to influence stakeholders and translate technical risk into business-facing insight * Excellent communication and strategic thinking for cross-functional alignment Key requirements *