Role: Senior Databricks Architect

Location : Toronto, ON

Mode: Contract

Required Skills

Databricks Data Engineering

Must have hands-on experience delivering at least one end-to-end Databricks implementation

Data Transformation & Data Pipeline DevelopmentExperience building and managing transformation pipelines in Databricks

AWS Cloud Platform

Solid understanding of AWS ecosystem; client environment is predominantly AWS

AWS Services (S3, Redshift, etc.)

Working knowledge of key AWS data services

Apache Spark / PySparkCore data engineering capability, preferably within Databricks

Strong Data Engineering Experience

Practical implementation experience, not just theoretical or presentation-level exposure

Problem-Solving / Delivery Mindset

Candidate should show depth of experience and ability to work across technologies

Job Responsibilities

1.Responsible for designing and implementing secure, scalable, and highly available cloud-based solutions on AWS.

2.Drive enterprise adoption of modern data and AI platforms, ensuring alignment between business objectives and technology initiatives.

3.Lead the architecture, design, and implementation of enterprise-scale data platforms leveraging Databricks on AWS.

4.Define overall data architecture strategy, release planning, governance frameworks, and platform roadmaps while partnering closely with customer stakeholders to accelerate modernization initiatives.

5.Provide strong technical leadership, customer-facing communication, and solution ownership from strategy through implementation.

6.Implement Databricks Agent Bricks to enable high-quality, domain-specific AI agents that continuously improve performance using enterprise data.

7.Design and implement scalable data warehouses, data lakes, and lakehouse architectures supporting reporting, analytics, AI,



and machine learning workloads.

8.Integrate Databricks Genie and AI/BI capabilities to deliver natural language analytics and self-service insights across the enterprise.

9.Hands-on experience with Databricks, Amazon, and PySpark for large-scale data engineering and analytics solutions.

10.Integrate Amazon S3, AWS Lake Formation, AWS DevOps pipelines, and Databricks workflows to achieve seamless end-to-end data and AI platform automation.

11.Experience integrating diverse structured, semi-structured, and unstructured data sources into enterprise Data Lakes and Data Warehouses.

12.Strong understanding of data modeling, data architecture, metadata management, data governance, and data quality best practices.

13.Ability to evaluate, compare, and articulate the advantages and trade-offs of various cloud, analytics, and AI platforms.

14.Collaborate with business and technology stakeholders to translate business requirements into scalable AWS-based data and AI solutions.

15.Define and implement AWS cloud governance, security, compliance, and operational best practices.

16.Identify opportunities to automate platform operations, deployment processes, monitoring, and data engineering workflows to improve efficiency and reliability.

17.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.

•Experience with Databricks Unity Catalog, Delta Lake, Mosaic AI, Genie, and Agent Bricks.

•AWS Solution Architect certification preferred.

•Experience delivering AI/GenAI, Lakehouse, Data Modernization, and Advanced Analytics initiatives for large enterprises.

•Strong consulting and stakeholder management experience.

📌 Senior Data Architect (Toronto)
🏢 Tekshapers
📍 Toronto