Senior Data Architect

• 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
• Strong 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.