Lead Azure Databricks engineering at Seaspan in a hands-on team leadership role focused on scalable data solutions and reliable delivery. Direct Data Engineers while shaping Lakehouse architecture, pipelines, and enterprise data products.

As Team Lead, Data Engineering, you will guide daily team direction and remain active in solution design, development, testing, troubleshooting, deployment, and production support. You will apply Python, SQL, Delta Lake, and Azure data services across batch and real-time pipelines. The role supports reporting, analytics, machine learning, AI, and data-driven applications through reusable dimensional models and enterprise integrations.

Key Responsibilities:

- Lead and directly manage Data Engineers
- Design scalable solutions using Azure Databricks and Delta Lake




- Build and optimize batch and real-time data pipelines
- Review code, troubleshoot issues, and support deployments
- Set technical direction, priorities, and engineering standards

Requirements:

- At least seven years in data engineering or related development
- Three years with Azure Databricks or comparable cloud platforms
- Robust Python, SQL, and dimensional modeling skills
- Experience leading, coaching, and reviewing Data Engineers
- Knowledge of governance, lineage, security, and access control

Bring technical leadership, Python, SQL, and Azure Databricks expertise to Seaspan’s enterprise data engineering team.

📌 Azure Databricks Data Engineering Lead (Vancouver)
🏢 Seaspan
📍 Vancouver