Cloud Data Engineer
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The role
Build and optimize scalable data pipelines on Databricks using PySpark to process large financial data for real-time analytics and reporting.
Design and implement ETL workflows for structured and semi-structured data from batch and streaming sources with Kafka, Airflow, and SQL.
Create Gold Layer transformations in Databricks to furnish high-quality datasets for BI and analytics, while ensuring data quality and governance.
Collaborate with data scientists, analysts, and stakeholders to deliver data solutions that meet business requirements.
Apply DevOps and CI/CD practices to data engineering workflows to improve reliability and deployment speed.
Optimize Spark jobs and SQL queries for performance and cost efficiency, while ensuring regulatory compliance for financial data.
Design and implement ETL workflows for structured and semi-structured data from batch and streaming sources with Kafka, Airflow, and SQL.
Create Gold Layer transformations in Databricks to furnish high-quality datasets for BI and analytics, while ensuring data quality and governance.
Collaborate with data scientists, analysts, and stakeholders to deliver data solutions that meet business requirements.
Apply DevOps and CI/CD practices to data engineering workflows to improve reliability and deployment speed.
Optimize Spark jobs and SQL queries for performance and cost efficiency, while ensuring regulatory compliance for financial data.
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