EY - GDS Consulting - AI And DATA -AI Data Platform Engineer - AI Data Platform Engineer - MS Fabric

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

EY-Consulting - Data and Analytics - AI Data Platform Engineer - MS Fabric - Senior EY’s Consulting Services is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional and technical capabilities and product knowledge. EY’s financial services practice provides integrated Consulting services to financial institutions and other capital markets participants, including commercial banks, retail banks, investment banks, broker-dealers & asset management firms, and insurance firms from leading Fortune 500 Companies. Within EY’s Consulting Practice, Data and Analytics team solves big, complex issues and capitalise on opportunities to deliver better working outcomes that help expand and safeguard the businesses, now and in the future. This way we help create a compelling business case for embedding the right analytical practice at the heart of client’s decision-making.

Role: AI Data Platform Engineer - MS Fabric

Experience Guide: 5-10 years

Primary Skill Area: Microsoft Fabric, OneLake, Lakehouse, Data Factory, Power BI Semantic Models & AI-Ready Data Products

The opportunity Build and operate enterprise-scale Data & AI platforms using Microsoft Fabric and the Azure data ecosystem. The role focuses on Fabric Lakehouse, Warehouse, OneLake, Data Factory pipelines, notebooks, Power BI semantic models, reusable platform engineering, APIs, Azure service integration, Git connectivity, Data SRE, data security, Immuta/Purview governed access, and AI/agentic enablement for modern analytics and GenAI workloads.

Your Key Responsibilities

• Microsoft Fabric Data Engineering

• Design and implement Fabric data solutions using OneLake, Lakehouse, Warehouse, Data Factory Pipelines, Dataflows, Notebooks, Spark, SQL endpoints, and Power BI semantic models.
• Build reusable ingestion and transformation frameworks for batch, event-driven, API-based, file-based, and enterprise application integration patterns.
• Develop curated data products across raw, standardised, trusted, and consumption layers with quality, lineage, and operational controls.

• Optimise pipeline performance, workspace usage, refresh patterns, capacity consumption, and downstream analytics readiness.

• Fabric & Azure Platform Engineering

• Create reusable platform standards for workspace onboarding, deployment pipelines, item naming, logging, monitoring, semantic model patterns, and support runbooks.
• Implement Git connectivity, branching strategy, pull requests, code reviews, CI/CD, Fabric REST API automation, and environment promotion.
• Integrate Fabric with Azure Data Lake Storage, Event Hubs, Functions, Key Vault, Azure DevOps, Azure Monitor, Microsoft Purview, Synapse, Databricks, and enterprise APIs.

• Support platform administration, release management, governance readiness, and production operations.

• AI, Copilot & Agentic Enablement

• Enable Fabric Copilot, AI-ready data products, semantic models, RAG-ready datasets, metadata-driven automation, and conversational analytics use cases.
• Support AI integration across Power BI, semantic layers, enterprise search, GenAI assistants, and downstream data consumers.

• Apply agentic operations for schema drift detection, failed pipeline summarisation, root-cause recommendation, data quality anomaly detection, and automated documentation.

• Governance, Security & Data SRE

• Implement Entra ID, workspace roles, item permissions, sensitivity labels, lineage, auditability, Key Vault integration, masking/security patterns, and controlled access.
• Integrate with Microsoft Purview, Immuta, Collibra, IAM, monitoring services, data quality tools, and enterprise access workflows.
• Build Data SRE dashboards for Fabric capacity, workspace usage, pipeline failures, refresh performance, data quality, cost, access activity, and SLA/SLO adherence.

Skills And Attributes For Success Skill / capability area

• Core platform: Microsoft Fabric, OneLake, Lakehouse, Warehouse, Data Factory Pipelines, Dataflows, Notebooks,…