Azure Data Solution Engineer

Microsoft Microsoft · Big Tech · Toronto, ON +1 · Digital Solution Engineering

This role focuses on designing and delivering modern, governed data platforms using Microsoft Fabric, Azure Databricks, and Azure SQL, enabling customers to modernize their analytics and data estates for AI-ready solutions. It's a technical sales role that guides organizations through data platform modernization, focusing on secure, scalable, and resilient cloud data architecture.

What you'd actually do

  1. Designing and delivering modern, governed data platforms using Microsoft Fabric (OneLake, Lakehouse, Data Warehouse, BI), Azure Databricks, and Azure SQL and OSS databases
  2. Partnering with customers to modernize analytics and data estates, enabling technical decision‑makers to confidently approve and adopt AI‑ready Azure data solutions
  3. Guiding organizations through data platform modernization—designing and optimizing governed, AI‑ready analytics solutions and translating technical capabilities into measurable business outcomes
  4. Collaborating across teams to deliver impactful solutions that enhance agility, reduce costs, and unlock value through AI-powered infrastructure
  5. Working directly with technical and business stakeholders to design and implement secure, scalable, and resilient architectures that support AI workloads and business-critical applications

Skills

Required

  • Designing and delivering modern, governed data platforms using Microsoft Fabric (OneLake, Lakehouse, Data Warehouse, BI), Azure Databricks, and Azure SQL and OSS databases
  • Modernizing analytics and data estates
  • Designing and optimizing governed, AI-ready analytics solutions
  • Designing secure, scalable, and resilient cloud data architecture
  • Technical sales
  • Data platform modernization
  • Azure data PaaS services
  • Translating technical capabilities into measurable business outcomes
  • Designing and modernizing Cloud & AI solutions on Azure
  • Leading technical migration and modernization discussions
  • Influencing technical decision makers
  • Understanding of hybrid and cloudnative architectures
  • Networking fundamentals
  • Azure security and compliance principles
  • Identity, networking security, data protection
  • Alignment to regulatory and compliance frameworks
  • Designing, validating, and explaining architectures
  • Collaboration skills
  • Continuous learning
  • Driving technical sales
  • Technical demos, proof of concepts, technical architecture accelerators
  • Leading architecture sessions and technical workshops
  • Building trusted relationships
  • Resolving technical blockers
  • Representing Microsoft in customer forums and technical communities
  • Proficiency in designing and delivering modern, governed data platforms using Microsoft Fabric (OneLake, Lakehouse, DW, BI), Azure Databricks, Azure SQL and OSS databases, data engineering pipelines, and Purview
  • Hands-on experience modernizing data platforms and analytics workloads on Azure
  • Lakehouse and modern data warehouse architectures
  • Legacy EDW/Hadoop modernization
  • Migration to Fabric-centric solutions
  • Understanding of end-to-end data architecture concepts
  • Ingestion (batch and streaming)
  • Storage, transformation, analytics, performance optimization, security, and data governance
  • Experience building and operating data engineering pipelines across Fabric and Databricks

What the JD emphasized

  • AI-ready Azure data solutions
  • AI-powered infrastructure
  • AI-driven business workloads
  • AI adoption
  • secure, scalable, and resilient cloud data architecture
  • modernize analytics and data estates
  • data platform modernization