Senior Data Quality Engineer

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Senior Data Quality Engineer to join our team in Bengaluru, Karnātaka (IN-KA), India (IN).

Role Overview

We are seeking a highly skilled Data Quality Engineer / Senior Quality Engineer with strong expertise in modern data platforms, ETL/ELT ecosystems, and quality engineering practices. The role involves validating end-to-end data pipelines, ensuring data integrity across cloud-based data warehouses, and developing scalable automation frameworks. The ideal candidate will also contribute to the quality assurance of analytical products, including dashboards, reports, and semantic data models.

Key Responsibilities

Design and execute comprehensive test strategies for ETL/ELT pipelines, data transformations, and data integration workflows. Validate data movement, completeness, accuracy, consistency, and lineage across source and target systems. Develop and maintain automated testing frameworks for data quality, reconciliation, and regression testing. Perform detailed data validation using advanced SQL queries across large and complex datasets. Validate Snowflake data warehouse solutions, including ingestion, transformation, and reporting layers. Collaborate with Data Engineers, Analysts, Product Owners, and Business stakeholders to define quality requirements. Implement and monitor data quality controls, reconciliation processes, and exception management mechanisms. Support CI/CD pipelines and integrate automated quality checks within DevOps processes. Validate business intelligence solutions, dashboards, reports, KPIs, and semantic models for accuracy and usability. Analyze defects, perform root cause analysis, and drive resolution with cross-functional teams. Contribute to continuous improvement of quality engineering standards, automation frameworks, and testing methodologies. Required Skills & Experience 8+ years of experience in Data Testing, ETL Testing, or Quality Engineering within data-centric environments. Strong expertise in Advanced SQL, including complex queries, joins, stored procedures, and performance optimization. Proven experience testing data pipelines and transformations in Snowflake environments. Hands-on experience with dbt (Data Build Tool), including model validation and data testing. Strong understanding of Data Warehousing concepts, Dimensional Modeling, and Data Vault architecture. Experience in ETL/ELT validation, data mapping, source-to-target reconciliation, and transformation testing. Expertise in designing and implementing test automation frameworks for data quality assurance. Strong knowledge of data reconciliation techniques, controls validation, and auditability requirements. Experience working with CI/CD pipelines, DevOps tools, and quality gate implementations. Strong analytical, problem-solving, and defect management skills with the ability to troubleshoot complex data issues. Excellent communication and stakeholder management skills with experience working in Agile environments. Desirable Skills Proficiency in Python for test automation, data validation, and quality engineering activities. Experience validating Power BI dashboards, reports, datasets, and semantic models. Exposure to cloud platforms such as Azure, AWS, or GCP. Knowledge of data governance, data lineage, metadata management, and compliance frameworks. Experience supporting analytics, reporting, and business intelligence solutions in enterprise environments.