Key Responsibilities:

Development and Deployment: Design, develop, and deploy data pipelines on Databricks to support data analytics.
Data Management: Manage and architect data storage solutions and ensure smooth ETL processes.
Collaboration: Work closely with data scientists and analysts to understand their data needs.
Performance Tuning: Optimize performance of data pipelines and improve Databricks jobs.
Monitoring and Debugging: Monitor data workflows and troubleshoot any issues that arise.
Documentation: Maintain clear documentation of data processes and technical designs.
Best Practices: Follow best practices in data governance, security, and privacy.

Job Requirements:

Experience: 6 to 15 years of experience in Data Engineering or related field preferentially with Databricks.
Technical Skills: Proficiency in Apache Spark, Python/Scala, and SQL is a must.
Databricks Experience: Hands-on experience working with the Databricks platform is required.
Data Modeling: Strong understanding of data modeling concepts and data warehousing principles.
Cloud Platforms: Familiarity with cloud services such as AWS, Azure, or GCP.
Collaboration Skills: Excellent communication and teamwork skills.
Problem Solving: Strong analytical and problem-solving abilities.