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You will be updated with latest job alerts via emailJob Requirements:
Experience: 810 years experience
1. Python ETL: The ideal candidate should have strong proficiency in Python programming language and experience in Extract Transform Load (ETL) processes. They should be able to design and develop efficient ETL workflows to extract data from various sources transform it as per business requirements and load it into target systems.
2. Azure Experience: The candidate should have handson experience working with Microsoft Azure cloud platform. They should be familiar with Azure services and tools and have a good understanding of Azure architecture and best practices.
3. Azure Data Factory DataBricks Azure Storage and Azure VM: The candidate should have practical experience with Azure Data Factory DataBricks Azure Storage and Azure Virtual Machines. They should be able to design and implement data pipelines using Azure Data Factory perform data transformations and analytics using DataBricks and manage data storage and virtual machines in Azure.
4. Data Governance Data Quality and Controls: The candidate should have a strong understanding of data governance principles data quality management and data controls. They should be able to implement data governance frameworks establish data quality standards and ensure compliance with data regulations and policies.
5. Implementing alerts and notifications for batch jobs: The candidate should have experience in setting up alerts and notifications for batch jobs. They should be able to configure monitoring and alerting mechanisms to ensure timely identification and resolution of issues in batch job execution.
Here are a few other notes I got from the call but this JD is very detailed as it relates to what theyre looking for.
Underlying work is helping migrate current pipeline from the server into Azure Data factory.
ETL and Azure Data Factory pipelines
Their goal is to use AI techniques to solve problems. 15 people in this team. Roy is 1st consultant hired for this project.
Full Time