Databricks Architect
Lead the architecture and implementation of enterprise-scale AWS Databricks platforms, focusing on scalable Lakehouse and Data Warehouse solutions. Drive data modernization initiatives and define technical standards for governance, security, and AI capabilities.
- On-site
- Toronto, ON
- Posted Aug 20, 2026
- Apply by Sep 19, 2026
- 1 position
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Job summary
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. Strong expertise in Databricks Data Engineering, ETL and data pipeline development. Strong AWS Cloud experience; AWS is the primary client environment. Hands-on experience with AWS S3, Redshift, Lake Formation and related data services. Strong 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. Strong 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.
What you’ll do
Lead the architecture and implementation of enterprise-scale AWS Databricks platforms, focusing on scalable Lakehouse and Data Warehouse solutions. Drive data modernization initiatives and define technical standards for governance, security, and AI capabilities.
Requirements
Requires over 12 years of experience in Data & Analytics with at least 5 years of hands-on Databricks architecture and a proven end-to-end implementation. Strong expertise in AWS services, PySpark, and data modeling is essential, with AWS Solution Architect certification preferred.
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Databricks Architecture
- AWS Cloud
- Apache Spark
- PySpark
- ETL
- Data Modeling
- Lakehouse Design
- Unity Catalog
- Delta Lake
- AWS S3
- AWS Redshift
- Lake Formation
- GenAI
- Stakeholder Management
- Data Governance
- Data Quality
Job areas
- Data & Analytics
- Technology
- Engineering
- Consulting
- Software
Additional details
- Minimum experience
- 12+ years
- Apply by
- Sep 19, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available