Job Responsibilities

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

- Drive enterprise adoption of up-to-date data and AI platforms, ensuring alignment between business objectives and technology initiatives.

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

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

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

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

- Design and implement scalable data warehouses, data lakes, and lakehouse architectures supporting reporting, analytics, AI, and machine learning workloads.

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

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

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

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





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

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

- Collaborate with business and technology stakeholders to 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, deployment processes, monitoring, and data engineering workflows to improve efficiency and reliability.

- 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.

Pay: $70.00-$72.00 per hour

Experience

- Databricks : 4 years (required)

- AWS: 3 years (required)

- Genie: 1 year (required)

- Agent Bricks: 1 year (required)

- Apache Spark / PySpark: 2 years (required)

Work Location: In person

📌 Senior Databricks Architect with AWS & Pyspark (Toronto)
🏢 Alchemy
📍 Toronto