Sr Databricks Engineer (Banking)

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Posted 22 hours ago

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About the role

  • Looking for a skilled Databricks Engineer to support a major data modernization project? Apply Now! Working with one of our top financial clients, this role cal

Responsibilities

  • Looking for a skilled Databricks Engineer to support a major data modernization project? Apply Now! Working with one of our top financial clients, this role calls for a Sr Databricks Engineer (Banking). The successful candidate will play a key role in transforming legacy platforms into modern, scalable data solutions on Azure Databricks, supporting enterprise-scale data workflows and modernization initiatives. Pay rate range (CAD): $70.00/hr – $75.00/hr Responsibilities Develop and maintain end-to-end data pipelines on Azure Databricks using Python and Spark. Implement and optimize data transformations aligned with the Medallion Architecture (Bronze, Silver, Gold). Automate workflows incorporating Azure Data Factory for data ingestion and processing. Monitor pipeline performance, troubleshoot issues, and optimize data workflows. Collaborate with cross-functional teams to support data modernization efforts and ensure seamless data delivery. Support migration from legacy systems to scalable cloud data architecture. Ensure data quality, security, and compliance standards are maintained throughout all phases of data processing. Document technical designs, processes, and workflows for ongoing support and enhancement. Desired Skill-Set Minimum of 5+ years of experience with Azure Databricks. Proficiency in Python programming. Strong knowledge of data modeling, data warehousing, and ETL best practices. Experience with automating data workflows using Azure Data Factory. Proven ability to monitor, troubleshoot, and optimize high-volume data pipelines. Hands-on experience with enterprise-scale data environments. Knowledge of cloud computing concepts and data security standards. Nice to Have Familiarity with SQL and data visualization tools. Experience working in financial services or regulated environments. Knowledge of other cloud platforms such as AWS or GCP. Exposure to DevOps practices for data pipeline deployment. Certification in Azure Data Engineering or similar.

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