Azure Oracle Data Engineer
Posted Updated
Summary
Data Engineer building and managing ETL pipelines and analytics data assets across Azure (Data Factory, Fabric) and Oracle (ODI, OCI, Oracle DB, SQL Server) environments, supporting Power BI reporting for a BC financial institution near North Cowichan.
Build Azure and Oracle data pipelines as a Data Engineer near North Cowichan, British Columbia, supporting reliable analytics and reporting.
This Data Engineer designs, builds, and manages data assets across Microsoft and Oracle environments. The work includes Azure Data Factory, Fabric, Oracle Data Integrator, SQL Server, Oracle Database, and Oracle Cloud Infrastructure. You will integrate datasets, develop data models, and support Power BI reporting.
Key Responsibilities:
Design scalable ETL pipelines across Microsoft and Oracle systems Manage databases, warehouses, and data lakes Implement data quality, security, and governance controls Develop models and schemas for analytics Support Power BI dashboards and curated reporting datasets Requirements:
Bachelor’s degree in computer science or related field Five years’ professional data engineering experience or equivalent Expertise in SQL, Python, data modeling, and integration Experience with Azure, SQL Server, Oracle, and OCI Strong analytical, communication, and problem-solving skills Apply data engineering expertise across Azure, Oracle, SQL, Python, and Power BI to strengthen organizational analytics.
Design scalable ETL pipelines across Microsoft and Oracle systems Manage databases, warehouses, and data lakes Implement data quality, security, and governance controls Develop models and schemas for analytics Support Power BI dashboards and curated reporting datasets Requirements:
Bachelor’s degree in computer science or related field Five years’ professional data engineering experience or equivalent Expertise in SQL, Python, data modeling, and integration Experience with Azure, SQL Server, Oracle, and OCI Strong analytical, communication, and problem-solving skills Apply data engineering expertise across Azure, Oracle, SQL, Python, and Power BI to strengthen organizational analytics.