DATA For AI

Job description

Please apply only if you are suitable for the job description below.

Required Skills & Experience

• 5+ years of experience in Data Quality Engineering, Analytics Testing, or Data driven transformation programs.
• 5+ years leading AI Data Assurance, AI/GenAI, Analytics, or AI Quality Engineering initiatives
• Strong knowledge of AI/ML, GenAI, LLMs, various RAG Architectures, Prompt Engineering, Vector Databases, DataOps/MLOps, and AI Governance.
• Strong expertise in ETL Testing, Analytics & BI Testing, Reporting Validation, AI Data Readiness Assurance, AI Data Harness Assurance, AI Data Outcome Assurance and Continuous AI Assurance
• Hands-on Experience with Cloud Data & AI Platforms such as Azure, AWS, GCP, Databricks, Snowflake, Microsoft Fabric, or similar.
• Strong leadership, stakeholder management, communication, and mentoring skills.

Technical & Professional Requirements

• Agile Delivery, Quality Governance
• AI Data Assurance, AI/ML, GenAI, LLMs & RAG Architectures
• Data Quality, Data Governance & Responsible AI
• ETL, Data Warehouse, Analytics, BI & Data Integration Testing
• SQL, Snowflake, Databricks, Informatica & Azure Data Factory (ADF)
• Prompt Engineering & Retrieval Assurance
• Python, PySpark & Test Automation
• Playwright, API Testing
• Vector Databases, AI Data Pipelines, DataOps & MLOps
• Azure, AWS & GCP Data & AI Platforms
• Jira, Zephyr, Azure DevOps & CI/CDRole & responsibilities

Preferred candidate profile

Perks and benefits