Design develop and maintain scalable secure and high-performance data pipelines using Azure Databricks and cloud-native services.
Build and optimize ETL/ELT workflows to support enterprise data integration requirements.
Develop cloud-based data solutions integrating structured and unstructured data sources.
Write clean reusable and efficient code in Python for data processing automation and orchestration.
Design and implement data models using normalization and denormalization techniques for OLTP and OLAP systems.
Manage and optimize cloud storage solutions such as Azure Data Lake and Blob Storage.
Monitor troubleshoot and resolve performance bottlenecks across data pipelines and ETL processes.
Support advanced analytics and Business Intelligence (BI) initiatives through robust data engineering practices.
Participate in code reviews and maintain best practices for source control using Git.
Contribute to enterprise data warehouse design and implementation.
Collaborate with cross-functional teams in an Agile environment and stay updated with emerging cloud and data engineering technologies.
Job Description: Design develop and maintain scalable secure and high-performance data pipelines using Azure Databricks and cloud-native services. Build and optimize ETL/ELT workflows to support enterprise data integration requirements. Develop cloud-based data solutions integrating stru...
Job Description:
Design develop and maintain scalable secure and high-performance data pipelines using Azure Databricks and cloud-native services.
Build and optimize ETL/ELT workflows to support enterprise data integration requirements.
Develop cloud-based data solutions integrating structured and unstructured data sources.
Write clean reusable and efficient code in Python for data processing automation and orchestration.
Design and implement data models using normalization and denormalization techniques for OLTP and OLAP systems.
Manage and optimize cloud storage solutions such as Azure Data Lake and Blob Storage.
Monitor troubleshoot and resolve performance bottlenecks across data pipelines and ETL processes.
Support advanced analytics and Business Intelligence (BI) initiatives through robust data engineering practices.
Participate in code reviews and maintain best practices for source control using Git.
Contribute to enterprise data warehouse design and implementation.
Collaborate with cross-functional teams in an Agile environment and stay updated with emerging cloud and data engineering technologies.