Databricks Data Engineer modernizing a Canadian enterprise data platform for reporting, analytics, and AI initiatives. Building scalable lakehouse pipelines, integrations, and transformations.
Responsibilities
Design, develop, and maintain data pipelines within the Enterprise Data Platform (EDP)
Build and optimize ETL/ELT processes for data ingestion, transformation, and integration
Use an Agentic approach to development and ensure outputs match development standards
Develop scalable and reusable data solutions using Databricks and cloud-based data technologies
Support migration and modernization from HANA environments to a modern data platform
Collaborate with Data Architects on scalable data models and platform solutions
Develop data transformation logic and workflows for business and analytics requirements
Ensure data quality, integrity, consistency, and performance
Troubleshoot data-related issues, bottlenecks, and performance concerns
Participate in code reviews, testing, deployment, and release activities
Work with business and analytics teams to understand requirements and deliver fit-for-purpose solutions
Contribute to platform best practices, documentation, and continuous improvement initiatives
Requirements
At least 3+ years of hands-on Databricks development experience
4+ years of overall Data Engineering, ETL, or Data Integration experience
Strong experience building ETL/ELT data pipelines and transformation processes
Proven experience working with large and complex datasets
Experience developing data solutions within cloud-based platforms
Solid understanding of data warehousing, data lake, and lakehouse concepts
Experience working in Agile delivery environments
Strong problem-solving and analytical skills
Excellent communication and collaboration abilities
Experience with Databricks, ETL/ELT development, data engineering, data integration, SQL, Python, data pipeline development, data transformation, and data warehousing concepts
Experience with Agentic frameworks and AI-assisted coding is a value add
Preferred: experience supporting large data platform initiatives, significant data migrations, Azure Data Services, Databricks Lakehouse architecture, modern data engineering frameworks, AI/GenAI/Machine Learning/advanced analytics, enterprise or consulting environments, data governance, metadata management, and data quality frameworks
Preferred technical knowledge: Azure Data Factory, Delta Lake, Spark/PySpark, Azure Synapse, data lake architecture, cloud data platforms, data governance and data quality, and CI/CD for data solutions
Applicants must state their work authorization in Canada
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