Azure Data & AI Architect

Role Overview

• Lead End‑to‑End Solution Delivery: Own delivery end‑to‑end: requirements → architecture → design → build → test → deployment
• Serve as the technical lead: set engineering standards, unblock delivery, and ensure quality across testing and release
• Design and implement AI solutions using Azure AI services (e.g., Azure OpenAI, Cognitive Services, Azure Machine Learning) and, where appropriate, Copilot / Copilot Studio
• Emphasize security, governance, and real‑world usability over experimentation for its own sake
• Build data platforms using Azure data services (ADF, Databricks, Synapse, ADLS) and/or Microsoft Fabric
• Deliver production‑grade pipelines (ETL/ELT), storage and compute patterns, and data models supporting BI and AI workloads
• Use Power Platform (Power Apps, Power Automate, Power BI) when it’s the right tool for rapid business value
• Partner with engineers and business stakeholders to translate requirements into buildable designs
• Coordinate with security and governance teams to ensure solutions meet best practices and client constraints
• Communicate architecture decisions — including tradeoffs — in plain language
• Act as a trusted advisor: align scope to outcomes, manage expectations, and keep clients informed when things change
• Create reusable internal assets (reference architectures, accelerators, playbooks) that improve delivery quality
• Stay current on Azure AI and data platform changes and apply learning pragmatically to client solutions
• Support early discovery, solution envisioning, and contribution to technical proposals, estimates, and SOWs as needed.

Requirements

• 10+ years delivering technology solutions, including 5+ years leading data engineering, analytics, or AI work on Azure
• Clear evidence of personal ownership — you can explain what you built, why you chose it, and what you’d change next time
• Hands‑on experience with Azure AI services and Azure data platforms and/or Microsoft Fabric
• Ability to design scalable patterns (lakes, warehouses, modeling) and integrate AI responsibly into workflows
• Practical operational mindset (CI/CD and MLOps experience is a plus)
• Comfortable working in ambiguity, making tradeoffs explicit, and keeping delivery moving without hand‑holding
• Strong client‑facing communicator who can explain complex decisions clearly and lead technical direction confidently
• Bachelor’s degree in Computer Science, Engineering, or equivalent professional experience
• Consulting or professional services background
• Power Platform and Power BI experience
• Microsoft Fabric and data governance familiarity
• Azure DevOps, CI/CD, and infrastructure‑as‑code experience
• Relevant Microsoft certifications
• Python used in real production systems
• Experience writing and maintaining code for data processing, automation, or model deployment.

Tech Stack

• Azure
• ETL
• Python