Sr Data Quality Assurance Specialist

Only apply if you can start ASAP (Start Date: 21st September)

The Senior Data Quality Assurance (QA) Specialist

Pune (Onsite)

Position Overview

The Senior Data Quality Assurance (QA) Specialist is responsible for ensuring the accuracy, completeness, consistency, and reliability of enterprise data assets, reporting solutions, and data integration processes. This role serves as the primary quality assurance resource for Power BI reporting, SQL-based data warehouses, ETL processes, and data integrations from internal and third-party systems.

The Senior Data QA Specialist will perform comprehensive validation of data pipelines, reports, dashboards, and database objects while proactively identifying and resolving data discrepancies across multiple systems. The position works closely with Data Engineers, BI Developers, Business Analysts, and business stakeholders to ensure data integrity throughout the data lifecycle.

Additionally, this role supports production operations through troubleshooting, root cause analysis, defect management, and resolution of data-related issues impacting business reporting and analytics. This position will report to the Director – Enterprise Data and BI.

Essential Functions

• Validate data accuracy, completeness, and consistency within enterprise SQL databases, data warehouses, and reporting environments.
• Develop and execute test plans, test cases, and validation procedures for new and existing data integrations.
• Perform end-to-end testing of ETL and ELT processes utilizing SQL and Python-based data pipelines.
• Verify source-to-target data mappings and transformations across multiple systems and applications.
• Conduct reconciliation and data balancing activities between source systems, staging environments, data warehouses, and reporting platforms.
• Identify, document, and track data quality issues and defects through resolution.
• Perform functional, regression, and data validation testing for Power BI reports, dashboards, data models, and datasets.
• Validate report calculations, KPIs, measures, dimensions, filters, hierarchies, and business logic.
• Ensure reporting output aligns with established business requirements and source system data.
• Verify report performance, data refresh processes, and security configurations.
• Collaborate with BI developers to resolve report defects and data inconsistencies.
• Investigate and troubleshoot production issues related to reporting, analytics, ETL processing, and data quality.
• Perform root cause analysis of data discrepancies detected by end users, business stakeholders, or automated monitoring processes.
• Support incident management processes through issue documentation, impact analysis, and resolution validation.
• Validate corrective actions and ensure production fixes meet business and technical requirements.
• Compare and validate data across transactional systems, operational databases, and analytical reporting solutions.
• Perform ad hoc data investigations to support business inquiries, audit requests, and operational reviews.
• Recommend improvements to data quality controls and monitoring procedures.
• Develop, maintain, and improve QA methodologies, testing standards, and validation frameworks.
• Assist in establishing data quality metrics and ongoing monitoring processes.

The above is not an all-inclusive list of all duties performed by this job title, only a representative summary of the primary duties and responsibilities. Incumbent may be required to perform other additional duties as assigned.

Minimum Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or related field.
• 5+ years of experience in Data Quality Assurance, Business Intelligence, Data Warehousing, Data Analysis, or related discipline.
• 3+ years of experience testing and validating enterprise reporting solutions, preferably Power BI.
• Strong hands-on experience with Microsoft SQL Server, SQL querying, and data analysis techniques.
• Experience validating ETL/ELT processes and data integrations.
• Working knowledge of Python-based data processing and automation solutions.
• Experience analyzing large datasets and identifying data quality issues across multiple systems.
• Demonstrated experience supporting production environments and investigating reported defects.
• Experience working with third-party data sources and enterprise applications.
• Understanding of data governance, master data management, and data lineage concepts.