Azure Databricks Data Engineer

TAL International Container Corporation
Louisville, KY, United States
11 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$72,800.0 - $93,600.0
Working hours
Regular working hours

Tech stack

Agile Methodology Data Analysis Microsoft Azure Continuous Integration Data Integration Software Debugging Scrum Methodology Azure Data Factory Data Lakes Enterprise Integration Data Management Data Pipelines
+1 more
Databricks

Job description

Work on Agile development projects and participate in sprint delivery. Design and implement data integration solutions in Microsoft Azure. Develop and maintain data pipelines using Azure Data Factory. Ingest data from various source systems into Azure. Perform data transformations using Azure Databricks and Delta Lake. Implement and maintain workflows using Prefect. Perform data analysis and troubleshooting for data-related issues. Assist in identifying and resolving data quality and pipeline issues. Collaborate with development teams to support CI/CD processes using Azure DevOps. Act as an individual contributor and problem solver. Participate in Agile ceremonies, sprint planning, and delivery activities.

Requirements

Experience developing and implementing data pipelines using Azure Data Factory (ADF). Experience ingesting data from multiple sources using Azure ADF. Experience transforming data using Azure Databricks and Delta Lake. Experience with Azure DevOps for CI/CD, including: Stories Bugs Issue management Experience implementing Prefect. Strong hands-on experience with Databricks. Experience working with Microsoft Azure integration solutions., Experience working in Agile development environments. Experience with sprint planning and sprint delivery. Strong analytical and problem-solving skills. Ability to work independently as an individual contributor.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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Key takeaways and accessing the Databricks developer toolkit

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