Senior Databricks Architect

Role: Senior Databricks Architect Location: North York, ON (5 days onsite) Duration: 6+ month Contract Role Overview: The candidate will lead the architecture and implementation of enterprise-scale AWS Databricks data platforms, including Data Lakes, Data Warehouses and Lakehouse solutions supporting Analytics, AI and Machine Learning initiatives. Key Responsibilities Design and implement secure, scalable and highly available cloud-based solutions on AWS. Lead the architecture, design and implementation of enterprise-scale data platforms leveraging Databricks on AWS. Define data architecture strategy, governance frameworks, release planning and platform roadmaps. Partner closely with customer stakeholders to drive data and technology modernization initiatives. Provide technical leadership, customer-facing communication and solution ownership from strategy through implementation. Implement Databricks Agent Bricks to enable domain-specific AI agents using enterprise data. Design and implement scalable Data Lake, Data Warehouse and Lakehouse architectures. Leverage Databricks Genie and AI/BI capabilities to enable natural-language analytics and self-service insights. Develop large-scale data engineering and analytics solutions using Databricks, AWS and PySpark. Integrate Amazon S3, AWS Lake Formation, AWS DevOps pipelines and Databricks workflows for end-to-end data and AI platform automation. Integrate structured, semi-structured and unstructured data sources into enterprise Data Lakes and Data Warehouses. Apply best practices in data modeling, data architecture, metadata management, data governance and data quality. Evaluate and communicate the advantages and trade-offs of different cloud, analytics and AI platforms. Translate business requirements into scalable AWS-based data and AI solutions. Define and implement AWS cloud governance, security, compliance and operational best practices. Identify opportunities to automate platform operations, deployments, monitoring and data engineering workflows. Lead architecture reviews, establish technical standards, mentor engineering teams and ensure successful delivery of enterprise-scale AWS Databricks programs. Preferred Experience: 12+ years in Data & Analytics with 5+ years of Databricks Architecture experience Databricks Unity Catalog, Delta Lake, Mosaic AI, Genie and Agent Bricks AWS Solutions Architect certification AI/GenAI, Lakehouse, Data Modernization and Advanced Analytics experience Strong consulting and stakeholder management experience Databricks Data Engineering with at least one end-to-end Databricks implementation Data Transformation and Pipeline Development AWS Cloud Platform and AWS data services Amazon S3, Redshift, Lake Formation, etc. Apache Spark / PySpark Enterprise Data Engineering Data Lakes, Data Warehouses and Lakehouse architectures Problem-solving and end-to-end solution delivery

Lead the architecture and implementation of enterprise-scale AWS Databricks data platforms, including Data Lakes and Lakehouse solutions. Drive data modernization initiatives and implement AI agents using Databricks Agent Bricks and Genie.

Requires over 12 years of experience in Data & Analytics with at least 5 years specializing in Databricks Architecture. Proficiency in AWS services, PySpark, and AI/GenAI capabilities is essential.

• Amazon Web ServicesPreferred

Identified from the job description. Confirm important requirements above.

• Databricks Architecture
• AWS
• PySpark
• Data Lakehouse
• Unity Catalog
• Delta Lake
• Mosaic AI
• GenAI
• Data Governance
• Data Modeling
• AWS Lake Formation
• Amazon S3
• Apache Spark
• Stakeholder Management
• Cloud Security
• DevOps Pipelines

• Data & Analytics
• Technology
• Software
• Consulting
• Engineering

Minimum experience

10+ years

Apply by

Sep 18, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available