Remote Cloud Engineer - Azure Databricks

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Job Overview

The Remote Cloud Engineer - Azure Databricks at Insight Global will play a pivotal role in designing, implementing, and optimizing data analytics solutions using Azure Databricks. This position will require collaboration with cross-functional teams to deliver scalable data solutions while ensuring performance, security, and reliability. The ideal candidate will possess an in-depth understanding of cloud architecture and will be responsible for maintaining the integrity and efficiency of our cloud environment while contributing to the overall data strategy of the organization.

Job Responsibilities

• Design, implement, and optimize data pipelines and workflows utilizing Azure Databricks.
• Collaborate with data scientists and analysts to ensure accuracy and reliability of data solutions.
• Monitor system performance, identify bottlenecks, and recommend improvements.
• Develop and enforce best practices for data processing, security, and governance.
• Provide technical support and guidance to team members on cloud-related issues.
• Participate in architectural reviews and contribute to the development of solutions on Azure.
• Stay updated with the latest Azure and Databricks features and enhancements to ensure best practices are employed in implementations.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 3+ years of experience in cloud engineering or cloud architecture, specifically with Azure.
• Proficiency in Azure Databricks and Databricks workflows.
• Strong knowledge of data engineering concepts, ETL processes, and data modeling.
• Experience with programming languages such as Python, Scala, or SQL.
• Familiarity with Azure services (e.g., Azure Data Lake, Azure SQL Database) and DevOps practices.
• Excellent communication skills and the ability to work within a collaborative team environment.

Technologies & Tools

The Remote Cloud Engineer - Azure Databricks will be utilizing a variety of technologies and tools including Azure Databricks for data analytics, Azure Data Lake for storage, Azure SQL Database for relational data management, and various data integration and ETL tools to streamline workflows. Familiarity with version control systems such as Git and CI/CD pipelines is also essential for maintaining a robust data environment.

Ideal Candidates

The ideal candidates should be proactive problem-solvers, capable of handling complex technical challenges while maintaining attention to detail. They should demonstrate strong analytical skills, a collaborative mindset, and the ability to thrive in a dynamic remote work environment. Candidates must exhibit a passion for continuous learning and innovation, as well as the capacity to adapt to evolving technologies and methodologies within cloud engineering.