Team Lead, Data Engineering - Databricks to lead and mentor a team of data engineers, conducting code reviews, design reviews, and knowledge-sharing sessio

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 Environment:

• 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 $135,000 - CAD $175,000