Azure Data Engineer

3 weeks ago


Daytona Beach, United States Futran Tech Solutions Pvt. Ltd. Full time
Title: Azure Data Engineer / Architect

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.
Skill Set
  • 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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