About The Position

This role will function as a Senior Principal Engineer for the Azure Data as a Service (DaaS) and Azure AI Infrastructure team. The position is responsible for researching, evaluating, designing, implementing, and maintaining enterprise Azure Data and AI platform solutions that are secure, scalable, resilient, and cost-optimized. This role requires deep and broad engineering experience with Microsoft Azure Data and Azure AI technology, with expertise in security, governance, and operational excellence.

Requirements

  • Bachelor’s degree in computer science, Information Security, or related field, or the equivalent education, training, and experience is desired.
  • Hands on experience designing, implementing and maintaining Azure Data PaaS services including Azure SQL, Synapse, Data Factory, Databricks, and ADLS Gen2.
  • Advanced expertise in configuring Azure security and governance using Azure Policy, RBAC, Private Endpoints, and Key Vault.
  • Experience in Azure cost optimization and capacity planning.
  • Strong verbal and written communication skills.
  • Proven ability to manage full-life-cycle IT initiatives.
  • Working knowledge of Infrastructure as Code (IaC) deployments using Azure Pipelines and/or terraform.

Nice To Haves

  • Experience with Azure AI services including Azure AI Foundry and AI Projects.
  • Exposure to AI/ML platform enablement or governance.
  • Microsoft Azure certifications (Data Engineer, Solutions Architect, or equivalent).

Responsibilities

  • Apply engineering principles to the design, enhancement, and operation of Azure Data and AI platform services.
  • Research, procure, deploy, configure, and support Azure Data and AI resources including platform dependencies.
  • Provide technical leadership in the architecture, design, and development of enterprise Azure Data and AI solutions.
  • Ensure the security and integrity of system and product solutions through secure-by-design architecture.
  • Anticipate and adjust for potential impact of platform changes, upgrades, and new service capabilities.
  • Anticipate, investigate, and resolve data platform performance and reliability issues by collaborating with Azure Infrastructure teams to identify root causes and implement improvements.
  • Provide guidance and technical support to customers onboarding applications to the Azure platform, assisting with Azure data service selection and usage to enable successful business outcomes.
  • Implement and enhance monitoring, logging, and alerting for Azure Data and AI platforms to support operational excellence and proactive issue detection.
  • Document new platform components and modifications to existing services and publishing standards.
  • Engineer Infrastructure as Code (IaC) deployments for Azure Data and AI resources.
  • Present clear, organized, and concise technical information to enable business decisions.
  • Lead, guide, and mentor less experienced engineers.
  • Participate in on-call rotation to provide support for business applications during business and off‑business hours.
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