Data Testing Cloud Consultant

Job Overview:

• We are looking for a Quality Engineering Lead to spearhead the execution of AI Data Assurance initiatives by guaranteeing high-quality and AI-ready data foundations that inspire trust.
• This position entails the formulation of quality strategies, the establishment of AI Data Assurance frameworks, the promotion of automation, and the assurance of high-quality AI-ready data foundations that facilitate reliable, responsible, and business-aligned AI outcomes.

Primary Responsibilities:

• Project Delivery Oversight
• Oversee the comprehensive delivery of AI Data Assurance programs
• Ensure delivery governance, quality metrics, executive reporting, and excellence in Agile Hybrid methodologies
• Quality Engineering and AI Assurance Governance
• Develop quality strategies, testing frameworks, and assurance processes for AI, ML, GenAI, AI data assurance, analytics, and BI platforms
• Manage end-to-end validation, release readiness, and quality gates
• Direct 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
• Enhance AI Data Outcome Assurance by assessing the quality, reliability, explainability, and business alignment of AI outputs
• Support Responsible AI, AI Governance, and Model Assurance initiatives
• Automation, Client Focus, and Team Leadership
• Create automation frameworks for AI Data Assurance, BI assurance, and ongoing quality monitoring
• Integrate quality controls and assurance gates within DataOps, MLOps, and CI/CD pipelines
• Lead and mentor teams in AI Data Assurance, fostering capability development, quality reviews, and continuous improvement
• Collaborate with business, product, data engineering, architecture, AI, ML, and platform teams to drive AI transformation initiatives
• Promote automation, AI-assisted testing capability development, and continuous improvement efforts
• Develop AI data assurance accelerators and engage in client demonstrations
• Contribute to client pursuits, solution proposals, estimations, and AI assurance offerings
• Establish partnerships, thought leadership assets, innovation frameworks, webinars, workshops, and knowledge-sharing initiatives

Technical Qualifications:

• Essential Skills and Experience
• A minimum of 5 years in Data Quality Engineering, Analytics Testing, or data-driven transformation programs
• At least 3 years of experience leading AI Data Assurance, AI, GenAI Analytics, or AI Quality Engineering projects
• In-depth knowledge of AI, ML, GenAI, LLMs, various RAG Architectures, Prompt Engineering, Vector Databases, DataOps, MLOps, and AI Governance
• Extensive 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
• Practical experience with Cloud Data AI Platforms such as Azure, AWS, GCP, Databricks, Snowflake, Microsoft Fabric, or similar
• Exceptional leadership, stakeholder management, communication, and mentoring abilities

Additional Qualifications:

• Technical and Professional Requirements
• Agile Delivery and Quality Governance
• AI Data Assurance, AI, ML, GenAI, LLMs, RAG Architectures
• Data Quality, Data Governance, Responsible AI
• ETL, Data Warehouse, Analytics, BI, and Data Integration Testing
• Familiarity with SQL, Snowflake, Databricks, Informatica, Azure Data Factory (ADF)
• Prompt Engineering and Retrieval Assurance
• Proficiency in Python, PySpark, Test Automation
• Experience with Playwright and API Testing
• Knowledge of Vector Databases, AI Data Pipelines, DataOps, MLOps
• Experience with Azure, AWS, GCP Data AI Platforms
• Familiarity with Jira, Zephyr, Azure DevOps, CI/CD

Preferred Skills:

Technology->AI-Responsible AI->Responsible AI->explainable AI, Technology->Data Services Testing->Big Data Testing, Technology->Experience Engineering->Generative UI/Dynamic UI