QA Engineer - Tech Lead

Overview

Validate the data pipelines and analytical reporting solutions for the Global Technology Services (GTS) Control Tower team, working with business intelligence, business analysis, data engineering, process engineering, governance and data analyst colleagues.

What you'll do

• Validate end-to-end ETL/ELT pipelines built on Azure/Microsoft Fabric platforms.
• Validate data movement across source, staging (Bronze/Silver) and consumption (Gold) layers.
• Ensure correctness of data transformations, aggregations and business rules.
• Execute data reconciliation testing between systems.
• Validate data completeness, duplicates, null values and integrity checks.
• Perform end-to-end validation of reports and dashboards built on Power BI semantic models, including data accuracy, KPI calculations, business logic, measures, aggregations, filters, slicers, drill-downs and user interactions.
• Perform functional and UI validation of dashboards and ensure data consistency between the semantic layer and reports.
• Create, maintain and execute test plans, test cases and test scripts, and automation scripts where applicable.
• Participate in STLC phases including requirement analysis, test design, execution and closure.
• Prepare test data and validate test scenarios.
• Identify, log, track and manage defects using JIRA, HP ALM or RTC, and collaborate with developers on resolution and retesting.
• Communicate testing progress, risks and results to stakeholders.
• Participate actively in Agile ceremonies: sprint planning, daily stand-ups, sprint reviews and retrospectives.
• Work closely with Data Engineers and business teams for requirement clarity and validation.

What you'll need

• 4 to 7 years of experience in QA / Testing roles.
• Strong understanding of ETL / Data Warehouse testing and data validation.
• Strong SQL expertise, including advanced querying and analytical functions.
• High attention to detail with focus on data quality and accuracy.
• Test management tools: JIRA, HP ALM or RTC.
• Understanding of the STLC process.

Nice to have

• Exposure to Microsoft Azure and cloud data platforms.
• Python.
• Understanding of the Financial Services / Banking domain (highly desirable).
• Experience testing data pipelines and reporting solutions end-to-end.
• Exposure to Microsoft Power BI / analytics platforms.
• Ability to identify data quality issues proactively.
• QA certifications such as ISTQB.