Azure Data Engineer
Overview
As an Azure Data Engineer you will be responsible for designing developing and deploying scalable data solutions using Azure native services with a strong focus on Azure Databricks. You will play a key role in building robust data pipelines optimizing data architectures and enabling advanced analytics for business-critical applications.
Key Responsibilities
Design & Build Data Pipelines: Develop manage and optimize robust and reliable data pipelines using Azure Data Factory Azure Databricks (PySpark/Scala) and other Azure services.
Databricks Implementation: Architect and implement end-to-end data processing solutions on Azure Databricks including batch and streaming data ingestion transformation and integration.
Data Modeling & Architecture: Design and build scalable data models (RDBMS and NoSQL) and architect data solutions with high performance reliability and security.
Productionizing Analytics: Bring data and analytics products to production ensuring solutions are scalable maintainable and aligned with business requirements.
Azure Data Engineer Overview As an Azure Data Engineer you will be responsible for designing developing and deploying scalable data solutions using Azure native services with a strong focus on Azure Databricks. You will play a key role in building robust data pipelines optimizing data architectures ...
Azure Data Engineer
Overview
As an Azure Data Engineer you will be responsible for designing developing and deploying scalable data solutions using Azure native services with a strong focus on Azure Databricks. You will play a key role in building robust data pipelines optimizing data architectures and enabling advanced analytics for business-critical applications.
Key Responsibilities
Design & Build Data Pipelines: Develop manage and optimize robust and reliable data pipelines using Azure Data Factory Azure Databricks (PySpark/Scala) and other Azure services.
Databricks Implementation: Architect and implement end-to-end data processing solutions on Azure Databricks including batch and streaming data ingestion transformation and integration.
Data Modeling & Architecture: Design and build scalable data models (RDBMS and NoSQL) and architect data solutions with high performance reliability and security.
Productionizing Analytics: Bring data and analytics products to production ensuring solutions are scalable maintainable and aligned with business requirements.
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