Senior Databricks Architect
Location: Toronto, ON – Hybrid (2–3 days onsite per week from Day 1)

Job Summary
We are seeking an experienced Senior Databricks Architect to lead the architecture, design, and implementation of enterprise-scale Data, Analytics, AI, and Lakehouse solutions on Databricks and AWS.
The ideal candidate will bring strong hands-on expertise in Databricks Data Engineering, Apache Spark/PySpark, AWS data services, data pipelines, and modern data architecture. This is a highly hands-on, customer-facing role requiring the ability to drive solutions from architecture and strategy through implementation and delivery.

Key Responsibilities
Lead the architecture, design, and implementation of secure, scalable, and highly available Databricks solutions on AWS.
Drive enterprise adoption of modern Data, Analytics, AI, and Lakehouse platforms aligned with business objectives.
Define overall data architecture, platform strategy, roadmaps, governance frameworks, and release planning.
Design and implement scalable Data Lakes, Data Warehouses, and Lakehouse architectures supporting analytics, reporting, AI, and machine learning workloads.
Build and manage large-scale data transformation and engineering pipelines using Databricks, Apache Spark, and PySpark.
Integrate AWS services including Amazon S3, AWS Lake Formation, Redshift, and DevOps/CI-CD pipelines with Databricks workflows.
Implement Databricks Unity Catalog, Delta Lake, Mosaic AI, Genie, and Agent Bricks capabilities where applicable.
Enable domain-specific AI agents using Databricks Agent Bricks and enterprise data.
Integrate Databricks Genie and AI/BI capabilities to support natural-language analytics and self-service insights.
Integrate structured, semi-structured, and unstructured data from diverse enterprise data sources.
Define and implement best practices for data modeling, metadata management, data governance, data quality, security, and compliance.
Evaluate cloud, analytics, data, and AI platforms and communicate architecture trade-offs to technical and business stakeholders.
Partner with business and technology teams to translate requirements into scalable AWS-based data and AI solutions.
Establish AWS governance, security, compliance, operational standards, and automation practices.
Identify opportunities to automate deployments, platform operations, monitoring, and data engineering workflows.
Lead architecture reviews, establish technical standards, mentor engineering teams, and ensure successful delivery of enterprise-scale programs.
Provide strong customer-facing communication, technical leadership, and end-to-end solution ownership.

Preferred Qualifications
12+ years of experience in Data & Analytics.
5+ years of Databricks architecture and implementation experience.
Strong hands-on experience with Databricks on AWS.
Experience with Unity Catalog, Delta Lake, Mosaic AI, Genie, and Agent Bricks.
Strong expertise in Apache Spark, PySpark, SQL, ETL/ELT, and large-scale data pipelines.
Experience with AWS S3, Redshift, Lake Formation, IAM, and AWS DevOps/CI/CD.
Experience delivering Lakehouse, Data Modernization, AI/GenAI, Advanced Analytics, and enterprise data platform initiatives.
Strong understanding of data governance, security, compliance, and enterprise data architecture.
AWS Solutions Architect certification is preferred.
Excellent consulting, stakeholder management, communication, and technical leadership skills.

Data Architect

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