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# QA Lead - ETL, Databricks & Agentic AI Testing-Chicago

- **Company:** E-Solutions
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Automation of Tests, Microsoft Azure, Big Data, Data Integrity, Extract Transform Load (ETL), Database Testing, Python (Programming Language), Standard Sql, SQL Databases, Software Testing Automation Framework, Strategies of Testing, Web Testing, Sql Optimization, Great Expectations (Foster Youth College-readiness and Support Program), Large Language Models, Agentic-AI, Pytest, Pyspark, Data Management, Machine Learning Operations, Databricks
- **Published:** October 11, 2026
- **Apply:** https://www.dice.com/job-detail/b08704b2-7d59-428d-a1c1-2ab336f4e9b3

## About the Role

* ETL & Data Testing
 * Advanced SQL
 * Azure Databricks / PySpark
 * Agentic AI / GenAI Testing & Evaluation
 * Web Testing
 * Test Automation Tools (pytest, Great Expectations, dbt, etc.)
 * Python Automation
 * Azure Boards, * 10+ years in ETL/Data Testing with ownership of test strategy.
 * Strong SQL, Databricks/PySpark, and Python automation expertise.
 * Experience with data reconciliation, migration validation, and test automation frameworks.
 * Exposure to healthcare data, PHI compliance, and large-scale data platforms.
 * Experience validating AI/Agentic systems is highly preferred.

Ideal Candidate: Senior QA professional with strong Data Testing, Databricks, SQL, Automation, and Agentic AI evaluation experience who can drive quality strategy and scalable validation across complex data platforms.

Senior QA Lead - ETL, Databricks & Agentic AI Testing-Chicago, IL (Hybrid - 3 days onsite)1etl,QA Lead,Databricks,Agentic AI TestingN/AC2CUnited States

## Description

* Define QA strategy, test plans, and reconciliation framework for large-scale data migration programs.
 * Validate source-to-target data across ETL pipelines and Databricks environments.
 * Build automated regression and data quality validation frameworks.
 * Evaluate AI/LLM-generated queries and transformation logic using MLflow or similar tools.
 * Ensure data integrity, compliance, security, and multi-tenant data isolation.
 * Lead QA efforts, mentor engineers, manage defects, and provide executive-level reporting.