Senior GCP Data QA Engineer

Job Summary:

We are looking for a Senior GCP Data QA Engineer to lead and execute data quality, reconciliation, and BI validation activities for a data lake migration to Google BigQuery and the migration of existing Power BI dashboards and reports to the new data platform. The role requires strong SQL expertise,hands-on experience with BigQuery and Power BI, and the ability to independently investigate complex data discrepancies, establish effective test coverage, and work closely with data engineering and BI teams to ensure accurate, reliable outcomes.

Key Responsibilities:

• Own end-to-end QA planning and execution for data migration, BigQuery datasets, ETL/ELT pipelines, and Power BI reports.
• Design and execute source-to-target reconciliation strategies, including record counts, aggregates, null checks, duplicate checks, business rules, and data completeness.
• Write, optimize, and review complex SQL queries using BigQuery Standard SQL and T-SQL to validate transformations, joins, aggregations, and business logic.
• Validate Power BI reports, datasets, DAX calculations, measures, filters, relationships, visuals, and Power BI Service behaviour after migration.
• Verify that migrated dashboards retain expected figures, business definitions, functionality, and acceptable report responsiveness.
• Test data transformations and pipeline outputs across ETL/ELT workflows; trace discrepancies from source systems through target tables and reporting layers.
• Investigate root causes of data mismatches and report defects, document evidence, assess impact, and coordinate fixes with data engineers and BI developers.
• Develop and maintain test scenarios, test cases, regression suites, reconciliation reports, defect logs, and QA sign-off documentation.
• Identify opportunities to automate repetitive validation and reconciliation using Python, SQL scripts, or suitable data-comparison tools.
• Define reusable data-quality checks and validation approaches to improve test coverage, consistency, and repeatability.
• Collaborate with business stakeholders to understand KPIs, reporting logic, acceptance criteria, and expected outputs.
• Provide technical guidance to QA team members, review validation results, and communicate risks, progress, and release readiness to stakeholders.

Required Skills:

• 6-8 years of experience in data QA, data testing, BI validation, data reconciliation, or data warehouse testing.
• Strong hands-on SQL skills, including complex queries in BigQuery Standard SQL and T-SQL.
• Practical experience with Google BigQuery and validating data in cloud-based data platforms.
• Hands-on Power BI experience, including reports, datasets, DAX, measures, filters, and Power BI Service.
• Strong understanding of data warehousing concepts, dimensional models, and ETL/ELT processes.
• Experience testing data migrations and validating source-to-target consistency across large datasets.
• Ability to analyse complex data discrepancies, perform root-cause investigation, and validate fixes.
• Experience designing test strategies, regression coverage, and structured QA documentation.
• Strong analytical and problem-solving skills, attention to detail, and clear communication with technical and business stakeholders.