Lead a team of quality engineers to develop and implement testing strategies for ETL processes, ensure data quality, and automate testing frameworks.
Project Role : Quality Engineering Lead (Test Lead)
Project Role Description : Leads a team of quality engineers through multi-disciplinary team planning and ecosystem integration to accelerate delivery and drive quality across the application lifecycle. Applies business and functional knowledge to develop end-to-end testing strategies through the use of quality processes and methodologies. Applies testing methodologies, principles and processes to define and implement key metrics to manage and assess the testing process including test execution and defect resolution.
Must have skills : Data Warehouse ETL Testing
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: We are looking for an experienced Data and AI ETL Tester to validate end-to-end data engineering solutions built on Databricks using Python/PySpark. The ideal candidate will be responsible for testing complex data transformation pipelines, ensuring data quality across the data warehouse and aggregated layers, validating reporting outputs, and contributing to the automation of testing processes. This role will also focus on testing metadata-driven frameworks and Agentic AI solutions designed for automated data quality management, metadata validation, and intelligent test generation. Roles & Responsibilities: - ETL and Data Pipeline Testing Validate ETL/ELT processes developed in Databricks (Python/PySpark) for correctness, performance, and scalability. Conduct data validation, reconciliation, and regression testing across staging, curated, and aggregated layers. Ensure consistency of data transformations between the data lake, warehouse, and reporting layers. Perform schema validation, business rule verification, and data lineage testing. Data Warehouse and Reporting Validation Validate data aggregation logic and ensure data accuracy in analytical and reporting layers. Cross-check BI reports/dashboards (e.g., Power BI, Tableau) against source and transformed data. Test data models, measures, and KPIs to ensure reporting accuracy. Data Quality and Metadata Testing Execute tests for data quality dimensions (accuracy, completeness, consistency, validity, timeliness, uniqueness). Validate metadata-driven frameworks that dynamically manage ETL logic and schema evolution. Test AI-driven or Agentic AI data quality frameworks—validating automation, intelligent rule generation, anomaly detection, and self-healing data flows. Test Automation and Framework Development Develop and maintain automated data testing frameworks using Python, PySpark, or Databricks notebooks. Integrate automated tests into CI/CD pipelines (e.g., Azure DevOps, Jenkins, GitHub Actions). Implement reusable test scripts for data validation, metadata verification, and data quality monitoring. Contribute to the test strategy, test planning, and execution for continuous integration and testing. Collaboration and Documentation Work closely with data engineers, data scientists, BI developers, and AI solution architects to ensure data accuracy and reliability. Create and maintain test plans, test cases, test data, and defect logs. Support root cause analysis and provide actionable insights to improve data quality and testing efficiency. Professional & Technical Skills:- 7+ years of experience in ETL or data testing, with strong understanding of data engineering principles. Experience in test automation using Python/PySpark and integrating with CI/CD pipelines. Strong expertise in data validation, data reconciliation, and testing large-scale data pipelines. Experience testing data warehouse aggregation layers and reporting outputs. Solid understanding of metadata-driven frameworks and data quality validation concepts. Familiarity with Agentic AI or AI-driven data quality automation tools. Hands-on experience with Databricks, Python, and PySpark. Strong SQL skills for data verification and troubleshooting. Working knowledge of data lakehouse architectures, Delta Lake, and data governance tools. Excellent analytical, communication, and problem-solving skills. Additional Information:- The candidate should have a minimum of 5 years of experience in Large Language Models. - This position is based at our Bengaluru office. - A 15 years full-time education is required. .15 years full time education
Project Role Description : Leads a team of quality engineers through multi-disciplinary team planning and ecosystem integration to accelerate delivery and drive quality across the application lifecycle. Applies business and functional knowledge to develop end-to-end testing strategies through the use of quality processes and methodologies. Applies testing methodologies, principles and processes to define and implement key metrics to manage and assess the testing process including test execution and defect resolution.
Must have skills : Data Warehouse ETL Testing
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: We are looking for an experienced Data and AI ETL Tester to validate end-to-end data engineering solutions built on Databricks using Python/PySpark. The ideal candidate will be responsible for testing complex data transformation pipelines, ensuring data quality across the data warehouse and aggregated layers, validating reporting outputs, and contributing to the automation of testing processes. This role will also focus on testing metadata-driven frameworks and Agentic AI solutions designed for automated data quality management, metadata validation, and intelligent test generation. Roles & Responsibilities: - ETL and Data Pipeline Testing Validate ETL/ELT processes developed in Databricks (Python/PySpark) for correctness, performance, and scalability. Conduct data validation, reconciliation, and regression testing across staging, curated, and aggregated layers. Ensure consistency of data transformations between the data lake, warehouse, and reporting layers. Perform schema validation, business rule verification, and data lineage testing. Data Warehouse and Reporting Validation Validate data aggregation logic and ensure data accuracy in analytical and reporting layers. Cross-check BI reports/dashboards (e.g., Power BI, Tableau) against source and transformed data. Test data models, measures, and KPIs to ensure reporting accuracy. Data Quality and Metadata Testing Execute tests for data quality dimensions (accuracy, completeness, consistency, validity, timeliness, uniqueness). Validate metadata-driven frameworks that dynamically manage ETL logic and schema evolution. Test AI-driven or Agentic AI data quality frameworks—validating automation, intelligent rule generation, anomaly detection, and self-healing data flows. Test Automation and Framework Development Develop and maintain automated data testing frameworks using Python, PySpark, or Databricks notebooks. Integrate automated tests into CI/CD pipelines (e.g., Azure DevOps, Jenkins, GitHub Actions). Implement reusable test scripts for data validation, metadata verification, and data quality monitoring. Contribute to the test strategy, test planning, and execution for continuous integration and testing. Collaboration and Documentation Work closely with data engineers, data scientists, BI developers, and AI solution architects to ensure data accuracy and reliability. Create and maintain test plans, test cases, test data, and defect logs. Support root cause analysis and provide actionable insights to improve data quality and testing efficiency. Professional & Technical Skills:- 7+ years of experience in ETL or data testing, with strong understanding of data engineering principles. Experience in test automation using Python/PySpark and integrating with CI/CD pipelines. Strong expertise in data validation, data reconciliation, and testing large-scale data pipelines. Experience testing data warehouse aggregation layers and reporting outputs. Solid understanding of metadata-driven frameworks and data quality validation concepts. Familiarity with Agentic AI or AI-driven data quality automation tools. Hands-on experience with Databricks, Python, and PySpark. Strong SQL skills for data verification and troubleshooting. Working knowledge of data lakehouse architectures, Delta Lake, and data governance tools. Excellent analytical, communication, and problem-solving skills. Additional Information:- The candidate should have a minimum of 5 years of experience in Large Language Models. - This position is based at our Bengaluru office. - A 15 years full-time education is required. .15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Top Skills
Azure Devops
Ci/Cd
Databricks
Github Actions
Jenkins
Pyspark
Python
SQL
Accenture Pune, Mahārāshtra, IND Office
Building B-1, Magarpatta City (SEZ, Mundhwa Rd, Magarpatta, Hadapsar, Pune, Maharashtra, India, 411013
Similar Jobs
Information Technology
Lead a team of quality engineers, develop testing strategies, ensure quality across applications, and monitor testing metrics for improvement.
Top Skills:
Micro Focus LoadrunnerNeotys Neoload
Information Technology
Lead a team of quality engineers to enhance testing processes, develop strategies for application quality, and drive continuous improvement initiatives.
Top Skills:
Neotys Neoload
Information Technology
Lead quality engineers in implementing testing methodologies and quality processes to enhance application delivery and performance, while mentoring the team and ensuring continuous improvement.
Top Skills:
AgileDevOpsNeotys Neoload
What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.
