Azure Tech Lead

We are looking for Azure Data Tech Lead for an enterprise scale client in Greater Toronto Area, Canada for an opportunity to work in state of the art, cutting edge technology environment.

Please apply with the resume clearly stating education and work experience including location of each assignment. Candidates must be authorized to work for any employer in Canada

Job Description

The Technical Lead will be responsible for driving the architecture, design, development, and delivery of modern cloud, data, and AI solutions. This role blends hands-on technical leadership with strategic oversight, guiding cross-functional engineering teams as they build scalable systems using Microsoft Azure, Databricks AI, and Snowflake Cortex. The Technical Lead will ensure adherence to enterprise security standards, streamline deployment processes, and provide architectural leadership across AI, integration, and cloud modernization initiatives.

Key Responsibilities:

• Lead solution design and implementation using Microsoft Azure Foundry, Databricks AI, and Snowflake Cortex.
• Architect and optimize data pipelines, AI workloads, and scalable cloud services.
• Ensure solutions align with enterprise standards, performance requirements, and data governance policies.
• Oversee environment setup, migration, redevelopment, and automated deployment pipelines.
• Implement CI/CD frameworks, IaC approaches, and repeatable deployment patterns.
• Ensure consistency and reliability across development, testing, and production environments.
• Lead development of AI-centric applications using:
• Prompt Engineering & Context Engineering
• Retrieval-Augmented Generation (RAG)
• AI Orchestration Frameworks
• LLMOps, AI Monitoring, and Evaluation (AI Evals)
• Design and integrate scalable APIs leveraging Azure API Management.
• Drive innovation by exploring new AI capabilities, large language models, and advanced analytics solutions.
• Lead teams through container-based solution development using Docker, Kubernetes, and cloud-native orchestration tools.
• Ensure optimized workload distribution, reliability, and resilience of deployed services.

Technical Expertise:

• Strong hands-on experience with:
• Azure Foundry
• Databricks AI / ML
• Snowflake Cortex & Snowflake ecosystem
• Azure API Management
• Cloud-native architecture
• Data engineering & MLOps
• RAG pipeline development
• AI evaluation and monitoring
• Containerization (Docker, Kubernetes)

Preferred Qualifications

• Microsoft Certified: Azure Solutions Architect / Azure AI Engineer
• Databricks Lakehouse Platform or AI Engineer
• Snowflake SnowPro certifications
• Experience in large enterprise cloud modernization programs.
• Background in LLM fine‑tuning, vector databases, and knowledge retrieval systems.