Databricks Data Engineering Role
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Summary
Senior Databricks data engineer building and maintaining large-scale ETL/ELT pipelines on Azure using Spark, SQL, and Python for a financial institution. Day-to-day work includes data cleansing, BI/reporting support, and implementing governance and security with Unity Catalog.
Enhance your data engineering skills as a Databricks Engineer focused on Azure cloud solutions. Utilize your extensive Spark experience to optimize and deliver large-scale data pipelines.
This role demands over 10 years of expertise in data engineering, particularly within financial institutions. You will design ETL/ELT pipelines and collaborate with various teams to drive analytic insights. Your work will prioritize governance, cost optimization, and performance to ensure compliance and high-quality data delivery.
Key Responsibilities: • Develop and maintain ETL/ELT data pipelines with Databricks • Cleanse and process data using Spark and SQL • Integrate data from sources like Azure Blob Storage • Work with teams to support BI and reporting initiatives • Implement governance and security measures with Unity Catalog
Requirements: • Over 10 years in data engineering roles • Experience in financial services or banking • Extensive knowledge of Databricks and Lakehouse Architecture • Proficient with Azure and Python programming • Familiarity with GitLab for version control
Bring your extensive expertise in Databricks and Azure cloud services to make a significant impact in this data engineering role.
This role demands over 10 years of expertise in data engineering, particularly within financial institutions. You will design ETL/ELT pipelines and collaborate with various teams to drive analytic insights. Your work will prioritize governance, cost optimization, and performance to ensure compliance and high-quality data delivery.
Key Responsibilities: • Develop and maintain ETL/ELT data pipelines with Databricks • Cleanse and process data using Spark and SQL • Integrate data from sources like Azure Blob Storage • Work with teams to support BI and reporting initiatives • Implement governance and security measures with Unity Catalog
Requirements: • Over 10 years in data engineering roles • Experience in financial services or banking • Extensive knowledge of Databricks and Lakehouse Architecture • Proficient with Azure and Python programming • Familiarity with GitLab for version control
Bring your extensive expertise in Databricks and Azure cloud services to make a significant impact in this data engineering role.