Lead Quality Assurance Engineer in Pune, भारत

About Onit

We're redefining the future of legal operations through the power of AI. Our cutting-edge platform streamlines enterprise legal management, matter management, spend management and contract lifecycle processes, transforming manual workflows into intelligent, automated solutions.

We’re a team of innovators using AI at the core to help legal departments become faster, smarter, and more strategic. As we continue to grow and expand the capabilities of our new AI-centric platform, we’re looking for bold thinkers and builders who are excited to shape the next chapter of legal tech.

If you're energized by meaningful work, love solving complex problems, and want to help modernize how legal teams operate, we’d love to meet you.

We are looking for a highly skilled and hands-on Lead Quality Engineer with strong expertise in data quality, analytics/report testing, ETL validation, SQL, and test automation .

The ideal candidate will have hands-on experience testing Tableau, Superset dashboards and reports , validating data across different layers of the data pipeline, and independently verifying business KPIs and metrics by writing SQL queries .

This role requires a strong understanding of the complete data lifecycle—from source systems through ETL/ELT pipelines and data warehouses to Tableau dashboards and reports . The candidate should be capable of identifying data discrepancies, performing reconciliation, validating transformation logic, and conducting root-cause analysis when reported metrics do not match underlying data.

This is a technical leadership role. The Lead Quality Engineer will provide guidance and mentorship to other Quality Engineers while remaining actively hands-on with SQL, data validation, automation, troubleshooting, and testing .

AI-assisted engineering is a mandatory part of this role. The candidate must have practical experience using AI engineering tools such as Cursor, Claude, or equivalent tools as part of their day-to-day work for test development, SQL generation, automation, troubleshooting, test-case creation, and productivity improvement.