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, Spark, Power BI semantic models.
• AI and GenAI: Fabric Copilot, AI-ready data products, semantic models, RAG, enterprise search, metadata automation, Agentic AI.
• Engineering: Python, PySpark, SQL, APIs, Git, CI/CD, Delta/Parquet, unit testing, integration testing, data pipeline testing.
• Azure and DevOps: Azure DevOps, Entra ID, Key Vault, Event Hubs, Functions, Azure Monitor, Purview, ADLS, deployment pipelines, policy-as-code.
• Governance and reliability: Purview, Immuta, sensitivity labels, lineage, audit, masking/security patterns, data quality, observability, Data SRE, FinOps.

 

To qualify for the role, you must have

• 5-10 years of experience in data engineering, data platform operations, analytics engineering, platform engineering, or AI platform enablement.
• Strong hands-on implementation experience with cloud data platforms, APIs, Git connectivity, CI/CD, governed access patterns, SRE practices, and production operations.
• Preferred certifications aligned to the relevant cloud/platform stack, data engineering, DevOps, security, governance, and AI/ML engineering.

 

Ideally, you'll also have

• Strong hands-on engineer with architecture awareness, delivery ownership, and a platform engineering mindset.
• Comfortable turning platform standards into reusable frameworks, secure implementation patterns, operational controls, and production-ready services.
• Able to mentor engineers, collaborate with architects/security/SRE teams, and adopt newer AI-native and agentic engineering methods.

 

What we look for

• Strong hands-on engineer with architecture awareness, delivery ownership, and a platform engineering mindset.
• Comfortable turning platform standards into reusable frameworks, secure implementation patterns, operational controls, and production-ready services.
• Able to mentor engineers, collaborate with architects/security/SRE teams, and adopt newer AI-native and agentic engineering methods.

 

What working at EY offers

At EY, we're dedicated to helping our clients, from start-ups to Fortune 500 companies, and the work we do with them is as varied as they are.

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasises high quality and knowledge exchange. Plus, we offer:

• Support, coaching and feedback from some of the most engaging colleagues around
• Opportunities to develop new skills and progress your career
• The freedom and flexibility to handle your role in a way that's right for you

 

 

EY | Building a better working world 

 
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.  

 
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.  

 
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.