SMARTWORK IT SERVICES LLC (SWITS)
Website:
smartworkitservices.com
Job details:
Job Title: Database Tester
Location: Bangalore, Pune, Chennai
Experience: 5-10 Years
Job Description
We are looking for a skilled
Data QA Engineer / Data Test Engineer with
5+ years of experience in data quality assurance, data validation, and testing enterprise data platforms. The ideal candidate should possess a strong foundation in
Data Engineering, with hands-on expertise in
Python, PySpark, SQL/T-SQL, Data Reconciliation, and Power BI validation. Experience working with
Microsoft Fabric, Databricks, Lakehouse, and Medallion Architecture is highly preferred.
The role involves validating migrated datasets, developing automated test frameworks, performing data reconciliation between legacy and modern data platforms, and ensuring the accuracy, consistency, and integrity of enterprise reporting solutions.
Roles & Responsibilities
- Design, develop, and execute end-to-end data validation and reconciliation strategies between legacy data platforms and Microsoft Fabric/Databricks environments.
- Perform apple-to-apple data reconciliation by comparing source and target datasets to ensure data accuracy, completeness, and consistency.
- Validate Cascade 2.0 business rules, column mappings, channel mappings, and transformation logic against source systems.
- Develop automated data quality, regression, and reconciliation frameworks using Python and PySpark.
- Write and optimize advanced SQL/T-SQL queries for data validation, reconciliation, and defect analysis across multiple environments.
- Validate Power BI reports, dashboards, datasets, filters, calculations, and Row-Level Security (RLS) to ensure accurate business reporting.
- Define and execute data quality checks, including row count validation, duplicate detection, null value validation, referential integrity, and business rule verification.
- Establish pass/fail criteria for data validation based on row counts, KPIs, key measures, and reconciliation thresholds.
- Identify, document, track, and resolve data quality issues and defects using defect management tools.
- Collaborate with Data Engineers, BI Developers, QA teams, and business stakeholders to resolve data discrepancies before production deployment.
- Perform regression, integration, system, and user acceptance testing (UAT) for enterprise data pipelines and reporting solutions.
- Participate in Agile ceremonies including sprint planning, daily stand-ups, sprint reviews, retrospectives, and defect triage meetings.
- Create and maintain comprehensive test plans, test cases, validation reports, reconciliation documents, and testing evidence.
Click on Apply to know more.