Design Azure cloud-native data platforms using Databricks and PySpark for end-to-end ingestion, processing, warehousing, analytics, and consumption needs.

This architect develops modern data solutions supporting data warehouses, BI, insights, and analytics. The work spans Azure, Databricks, PySpark, data governance, and cloud-native architecture. You will address modernization, scalability, performance, flexibility, and cost-effectiveness across complex data environments.

Key Responsibilities:

- Develop modern cloud-native data solutions and architectures
- Build cost-effective Databricks infrastructure and orchestrate Azure workflows
- Lead data strategy sessions on scalability and performance
- Create Databricks CI/CD pipelines using Azure DevOps




- Implement customer data modernization solutions

Requirements:

- 15+ years of experience, including four years implementing cloud-native data solutions
- Experience with Azure, Databricks, PySpark, and contemporary data platforms
- Proficiency in cloud-native architecture and data governance
- Experience migrating Spark and Hadoop environments to Databricks
- Understanding of data warehouses, cloud databases, and columnar architectures

Apply Azure architecture, Databricks engineering, and governance expertise to deliver scalable modern data platforms and analytics solutions.

📌 Azure Cloud Data Architect (Canada)
🏢 Envision Technology Solutions
📍 Canada