Key Requirements
12+ years of experience in Data & Analytics.
5+ years of hands-on Databricks Architecture experience.
Must have delivered at least one end-to-end Databricks implementation.
Robust expertise in Databricks Data Engineering, ETL and data pipeline development.
Solid AWS Cloud experience; AWS is the primary client environment.
Hands-on experience with AWS S3, Redshift, Lake Formation and related data services.
Robust Apache Spark / PySpark expertise.
Experience designing Data Lakes, Data Warehouses and Lakehouse solutions.
Strong understanding of Data Modeling, Data Architecture, Metadata, Governance and Data Quality.
Experience with Databricks Unity Catalog and Delta Lake.
Exposure to Mosaic AI, Databricks Genie and Agent Bricks.
Experience with AI/GenAI, Data Modernization and Advanced Analytics is preferred.
Robust consulting, stakeholder management and communication skills.




Excellent problem-solving and delivery mindset.
AWS Solution Architect Certification is preferred.

Responsibilities
Lead architecture and implementation of enterprise-scale AWS Databricks platforms.
Design scalable and secure Lakehouse, Data Lake and Data Warehouse architectures.
Build and optimize Databricks data transformation and pipeline solutions.
Integrate AWS S3, Lake Formation, DevOps pipelines and Databricks workflows.
Drive data and AI platform modernization initiatives.
Implement Databricks Genie, AI/BI and Agent Bricks capabilities.
Define architecture strategy, governance, security and technical standards.
Lead architecture reviews and mentor engineering teams.
Partner with business and technical stakeholders to deliver enterprise solutions.

📌 Databricks Architect North York (Canada)
🏢 Xaxis Solutions
📍 Canada