Azure Data Engineer
3 weeks ago
Location: Daytona FL 3 Days Hybrid
Duration Longterm contract
Need 11+ Years of Experience Required
Scope of Work
- Deep understanding of Azure Cloud Platform and Engineering, Infrastructure setup and configuration, tools and services, Data access and sharing, and hands-on work.
- Key objectives Include tasks such as designing and maintaining Databricks infrastructure, optimizing data engineering workflows, and ensuring data quality and governance.
- Deep understanding of Databricks tools and products like Delta Tables, Delta Like Tables, Unity Catalog, Serverless execution and setup and configuring experience.
- The technical skills and expertise required for the role, such as proficiency in Databricks, Apache Spark, cloud platforms (Azure), programming languages (Python, Scala, Java), data modeling, and database design.
- Collaboration with other team members, such as data scientists, data engineers, and business stakeholders. Emphasize the need for effective communication, documentation, and knowledge sharing within the team.
- The expected outcomes and performance indicators for the Databricks Engineer. This could include metrics such as data processing efficiency, data quality improvements, and successful project completion.
- 3-4 Years of working experience on Azure Platform - Infra, tools and services
- 2-3 years of experience on optimize and tune Databricks clusters for performance, scalability, and reliability for data engineering workloads.
- Develop and maintain ETL pipelines to extract, transform, and load data from various sources into Databricks.
- Hands-on working experience on Python/PySpark using Databricks Notebooks and Workspace.
- Experience in troubleshoot and resolve Databricks-related issues and provide technical support to users.
- Architect and Design, Databricks deployment strategy and experience on data engineering tasks, including data processing, transformation, and integration.
- Implement Azure data engineering best practices, including data quality checks, data lineage, and data governance, within the Databricks environment.
- Leverage Azure DevOps and CI/CD best practices to automate the deployment and management of data pipelines and infrastructure
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