Databricks Data Engineer / Developer (PL 866)

Location: Remote within Canada Client: Consulting Client Contract Duration: 6 months contract MUST HAVE: 3+ years of hands-on Databricks development experience. 4+ years of overall Data Engineering, ETL, or Data Integration experience. Overview Our consulting client is seeking a Databricks Data Engineer / Developer to support a strategic Enterprise Data Platform (EDP) transformation initiative. The organization is modernizing its enterprise data landscape and building a next-generation data platform leveraging Databricks and modern cloud-based architecture. This role will play a key part in designing, developing, and implementing scalable data solutions that support enterprise reporting, analytics, AI initiatives, and future data-driven capabilities. The ideal candidate will possess strong data engineering expertise, hands-on Databricks development experience, and a solid understanding of ETL/ELT processes, data integration, and modern data architecture. This individual will work closely with data architects, project managers, analysts, and business stakeholders to deliver high-quality data solutions within a rapidly evolving environment. Key Responsibilities - Design, develop, and maintain data pipelines within the Enterprise Data Platform (EDP). - Build and optimize ETL/ELT processes to support data ingestion, transformation, and integration requirements. - Make use of an Agentic approach to development and ensure that output matches development standards. - Develop scalable and reusable data solutions using Databricks and cloud-based data technologies. - Support migration and modernization activities from HANA environments to a modern data platform. - Collaborate with Data Architects to implement scalable data models and platform solutions. - Develop data transformation logic and workflows to support business and analytics requirements. - Ensure data quality, integrity, consistency, and performance across platform solutions. - Troubleshoot and resolve data-related issues, bottlenecks, and performance concerns. - Participate in code reviews, testing, deployment, and release activities. - Work closely with business and analytics teams to understand data requirements and deliver fit-for-purpose solutions. - Contribute to platform best practices, documentation, and continuous improvement initiatives.