Azure Data and AI Strategy Customer Engineer

Job Overview

We are seeking an Azure Data & AI Strategy Expert to guide enterprise customers through modern data estate modernization and AI enablement using Microsoft’s Azure data platform.

Responsibilities

• Guide enterprise customers in designing governed data foundations using Azure Purview, Microsoft Fabric, and Databricks.
• Lead workshops and strategy sessions around data readiness for AI, including architecture reviews, risk assessments, and value roadmaps.
• Support customer adoption of Microsoft Fabric by advising on lakehouse strategies, real-time pipelines, and integration with Power BI and Copilot.
• Provide advisory on integrating Databricks with the broader Microsoft data stack and establishing enterprise-scale ML ops foundations.
• Support the implementation of AI Foundry scenarios, ensuring data quality, governance, and cost optimization across AI solutions.
• Advocate for secure and responsible AI deployment strategies across the data lifecycle.

Requirements

• 10+ years of IT experience
• 7+ years of experience in data architecture, governance, or enterprise analytics strategy
• Familiarity with Microsoft Fabric, Databricks, and the Azure data platform
• Experience advising on data modernization projects, particularly in AI-adopting enterprises
• Solid understanding of data governance principles, business metadata, and operational AI enablement
• Executive presence with ability to translate complex data infrastructure into business value narratives

Key Skills & Technologies

• Data Governance: Azure Purview (catalog, lineage, quality scans, domains)
• Data Platforms: Microsoft Fabric (OneLake, Data Factory, Data Activator, Real-Time Hub), Databricks, Azure Synapse
• AI Enablement: Azure AI Foundry, model lifecycle readiness, AI observability
• Architecture: Lakehouse, Delta Lake, Spark, Power BI integration
• Security & Compliance: Data protection strategy, labeling, role-based access, audit trails
• Strategy: Cloud Adoption Framework, Responsible AI principles, FinOps-aware design