Futran Tech Solutions Pvt. Ltd.
Azure Databricks Admin /Architect
Futran Tech Solutions Pvt. Ltd., Daytona Beach, Florida, United States, 32118
Azure Databricks Admin (Onsite)
Location: Daytona Beach, FL
No remote, Need to work from the Daytona office.
Duration Longterm contract
Scope of WorkDeep 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 services2-3 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
Location: Daytona Beach, FL
No remote, Need to work from the Daytona office.
Duration Longterm contract
Scope of WorkDeep 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 services2-3 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