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Data Testing Cloud Consultant
Infosys · Bangalore, India
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We are seeking a Quality Engineering Lead to drive the delivery of AI Data Assurance initiatives by ensuring trusted, high-quality, and AI-ready data foundations. This role is responsible for defining quality strategies, establishing AI Data assurance frameworks, driving automation, and ensuring trusted, high-quality, AI-ready data foundations that enable reliable, responsible, and business-aligned AI outcomes. Responsibilities Project & Delivery Leadership
- Lead end-to-end delivery of AI Data Assurance programs.
- Drive delivery governance, quality metrics, executive reporting, and Agile/Hybrid delivery excellence. Quality Engineering, AI Assurance & Governance
- Define quality strategies, testing frameworks, and assurance processes for AI/ML, GenAI, AI data assurance, analytics, and BI platforms.
- Govern end-to-end validation, release readiness, and quality gates.
- Lead testing and validation of data platforms, pipelines, analytics solutions, BI platforms and AI-ready datasets.
- Implement AI Data Harness Assurance across data pipelines, RAG systems, vector stores, and AI workflows.
- Drive AI Data Outcome Assurance by evaluating AI output quality, reliability, explainability, and business alignment.
- Support Responsible AI, AI Governance, and Model Assurance initiatives. Automation, Client Orientation & Team Leadership
- Build automation frameworks for AI Data Assurance, BI assurance and continuous quality monitoring.
- Embed quality controls and assurance gates within DataOps, MLOps, and CI/CD pipelines.
- Lead and mentor AI Data Assurance teams and drive capability development, quality reviews, and continuous improvement.
- Collaborate with business, product, data engineering, architecture, AI/ML, and platform teams to deliver AI transformation initiatives.
- Drive automation, AI assisted testing, capability development, and continuous improvement initiatives.
- Build AI data assurance accelerators and participate in client demos
- Contribute to client pursuits, solutioning, proposals, estimations, and AI assurance offerings.
- Build partnerships, thought leadership assets, innovation frameworks, webinars, workshops, and knowledge-sharing initiatives. Technical requirements Required Skills & Experience
- 5+ years of experience in Data Quality Engineering, Analytics Testing, or Data driven transformation programs.
- 3+ 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 "Location will be based on business requirement." Additional responsibilities 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/CD Education Bachelor of Engineering