Permanent Full Time Hybrid (3 days in the office) Must Haves: 8+ years of experience in data engineering 3+ years of hands-on experience with Databricks platform Proven experience leading a team Strong expertise in Python and Spark programming Demonstrable experience in using AI in development Proven experience with AWS or other similar cloud services Deep understanding of data modeling and SQL Experience with Delta Lake and Lakehouse architecture Strong knowledge of ETL/ELT principles and patterns Experience with version control systems (Git) Demonstrated ability to optimize data pipelines Strong problem-solving and analytical skills Excellent communication and collaboration abilities Nice to Have: Financial services industry experience Experience with multiple cloud providers Knowledge of AI/ML implementation patterns API development experience Experience with real-time data processing Data governance framework experience What Sets You Apart: Active interest in emerging technologies and industry trends Experience implementing complex data solutions Track record of continuous learning and skill development Strong technical documentation abilities Experience using AI tools to enhance productivity Ability to mentor junior team members Technical Workplace:



Primary Platform: Databricks Cloud Platform: AWS (S3, Glue, Lambda) Languages: Python, SQL Tools: Delta Lake, Unity Catalog, Git Additional: Real-time processing, API integrations Responsibilities Your Role: You will lead and mentor a team of data engineers, conducting code reviews, design reviews, and knowledge-sharing sessions across multiple locations Drive the Agile/Scrum SDLC process and collaborate with team members Design and develop Databricks solutions leveraging Lakehouse architecture for enterprise data processing and analytics Develop and optimize ETL/ELT pipelines Create and manage structured streaming pipelines for real-time data processing Configure and optimize Databricks clusters and Spark jobs for optimal performance Utilize Delta Live Tables for data ingestion and transformations Apply Unity Catalog features and IAM best practices for security governance and access control Support infrastructure and resource management using Terraform Implement monitoring solutions for pipeline performance and data quality Contribute to code reviews and knowledge-sharing sessions Salary Range: CAD $, - CAD $,

📌 Team Lead, Data Engineering - Databricks to lead and mentor a team of data engineers, conducting code reviews, design reviews, and knowledge-sharing sessions across multiple locations (Toronto)
🏢 S.i. Systems
📍 Toronto