Job Description:
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Design develop and manage scalable and secure data pipelines using Databricks and PySpark.
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Architect and implement cloud-based data solutions integrating structured and unstructured data sources.
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Write clean efficient and reusable code primarily in Python for cloud automation data processing and orchestration.
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Build and optimize ETL workflows and ensure seamless data integration across platforms.
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Develop data models using normalization and denormalization techniques to support OLTP and OLAP systems.
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Troubleshoot performance bottlenecks in data flows and ETL processes.
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Integrate advanced analytics and support BI use cases within the Cloud ecosystem.
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Lead code reviews and ensure adherence to version control practices (e.g. Git).
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Contribute to the design and deployment of enterprise-level data warehousing solutions.
-
Stay current with Cloud technologies and Python ecosystem updates to adopt best practices and emerging tools.
Job Description: Design develop and manage scalable and secure data pipelines using Databricks and PySpark. Architect and implement cloud-based data solutions integrating structured and unstructured data sources. Write clean efficient and reusable code primarily in Python for cloud auto...
Job Description:
-
Design develop and manage scalable and secure data pipelines using Databricks and PySpark.
-
Architect and implement cloud-based data solutions integrating structured and unstructured data sources.
-
Write clean efficient and reusable code primarily in Python for cloud automation data processing and orchestration.
-
Build and optimize ETL workflows and ensure seamless data integration across platforms.
-
Develop data models using normalization and denormalization techniques to support OLTP and OLAP systems.
-
Troubleshoot performance bottlenecks in data flows and ETL processes.
-
Integrate advanced analytics and support BI use cases within the Cloud ecosystem.
-
Lead code reviews and ensure adherence to version control practices (e.g. Git).
-
Contribute to the design and deployment of enterprise-level data warehousing solutions.
-
Stay current with Cloud technologies and Python ecosystem updates to adopt best practices and emerging tools.
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