AI-Driven QA Lead for BI & Data Automation

Groupe Kardol; Manhattan Beach (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

InfoCepts LLC seeks a Quality Engineer Lead to embed an AI-native, automation-first QE capability within the BI development lifecycle. You will champion agentic automation across data validation, regression engineering, and autonomous defect management to deliver faster, more reliable BI releases.

You will oversee data validation across pipelines, build reusable QA assets, and ensure observability for accuracy, integrity, and performance of BI assets.

Qualifications

• Design and implement automated test strategies across functional, non-functional, regression, and data validation scope.
• Proven experience leveraging AI agents for automated test case generation and autonomous defect validation.
• Strong automation mindset for BI and data testing, minimizing manual QA.
• Extensive experience in end-to-end validation of dashboards, reports, KPIs, and underlying data.
• Proven experience in end-to-end testing including ETL and BI testing.
• Excellent SQL and Python skills.
• Experience designing profiling rules and data reconciliations to ensure data accuracy across pipelines.
• Hands-on ability to create detailed and comprehensive test cases for data, functional, and performance testing.

Responsibilities

• Automation-First Test Planning and Execution across BI scope.
• Lead embedded QE POD within BI delivery and drive automation-first practices.
• Provide quality governance through scorecards on coverage, cycle time, and defects.

Skills

Automation testing

AI agents

BI testing

SQL

Python

Data validation

End-to-end testing

ETL testing

Test case design

Education

Bachelor's degree in computer science or related field

Tools

SQL

Python

Job description

InfoCepts LLC seeks a Quality Engineer Lead to embed an AI-native, automation-first QE capability within the BI development lifecycle. You will champion agentic automation across data validation, regression engineering, and autonomous defect management to deliver faster, more reliable BI releases.

You will oversee data validation across pipelines, build reusable QA assets, and ensure observability for accuracy, integrity, and performance of BI assets.