Senior Data Engineer

Job Title: Senior Data Engineer – Databricks Job Type: 6-month contract to permanent Location: Vancouver, BC (Hybrid, 3 days in-office) Hours per week : 40 hours per week Rate: $60/hr Inc. ($115K to $120K when it converts to permanent) Overview Our client is embarking on a transformative data journey to consolidate their data infrastructure into a unified Databricks Lakehouse platform. As a Senior Data Engineer, you will lead the technical implementation of their Databricks migration, establishing foundational data architecture, and mentoring team members to build a scalable, reliable data ecosystem. This role is critical for designing and implementing a comprehensive data strategy that drives business value through advanced analytics and AI capabilities. Responsibilities Design and implement a medallion architecture (bronze, silver, gold) within Databricks to support data transformation, quality, and accessibility Develop robust ETL/ELT pipelines to ingest data from various sources, including the SQUARE Point of Sale (POS) system and our ERP (INforce) Establish governance frameworks using Unity Catalog to ensure data security, compliance, and proper access controls Collaborate with business stakeholders to standardize business definitions and logic through a well-designed semantic layer Mentor and upskill team members on Databricks technologies, best practices, and modern data engineering techniques Optimize data pipelines for performance and cost efficiency in cloud environments Implement data quality monitoring and testing frameworks to ensure reliable analytics Enable a single source of truth across the organization by consolidating disparate data sources into a unified Lakehouse platform Accelerate business decision-making through standardized metrics and efficient data processing Establish a foundation for advanced analytics, AI/ML capabilities, and forecasting Build a scalable data architecture that supports the company’s long-term data strategy Create a culture of data excellence by mentoring team members and establishing best practices Drive the successful implementation of multi-phase data migration from legacy systems to modern cloud architecture Qualifications: 5 years of experience in data engineering, with at least 2 years of hands-on experience with Databricks Strong proficiency in Python and SQL for data transformation and pipeline development Experience implementing medallion architecture and Delta Lake in production environments Practical knowledge of Unity Catalog and data governance frameworks Experience with cloud platforms, preferably AWS Demonstrated ability to mentor junior team members and communicate technical concepts effectively Experience with data modeling and implementing semantic layers Familiarity with data visualization tools (Power BI preferred) Experience migrating data from on-premises systems to cloud environments Databricks certification (e.g., Databricks Certified Data Engineer) is a plus