Data Engineer

• Design, build, and enhance data pipelines using Databricks Runtime, Delta Lake, Autoloader, and Structured Streaming
• Implement secure and governed data access protocols utilizing Unity Catalog, workspace controls, and audit configurations
• Manage and integrate structured and unstructured data from diverse sources, including APIs and cloud storage
• Develop and maintain notebook-based workflows and manage jobs using Databricks Workflows and Jobs
• Apply best practices for performance tuning, scalability, and cost optimization in Databricks environments
• Collaborate with data scientists, analysts, and business stakeholders to deliver clean and reliable datasets
• Support continuous integration and deployment processes for Databricks jobs and system configurations
• Ensure high standards of data quality and security across all engineering tasks
• Troubleshoot and resolve issues to maintain operational efficiency in data pipelines

• 5–7 years of experience in data engineering or software development roles
• At least 3 years of hands-on experience with Databricks, Delta Lake, and Spark (PySpark, PySQL, Python)
• Proven expertise in implementing and managing Unity Catalog in multi-tenant environments
• Strong knowledge of big data performance optimization techniques and cloud-based systems
• Familiarity with GitHub, CI/CD pipelines, and automated deployment for Databricks assets
• Experience with cloud storage services such as Azure or AWS, including networking configurations
• Excellent problem-solving abilities and a demonstrated capacity to thrive in Agile team environments

Databricks Certified Data Engineer certification is highly preferred

• medical, vision, dental, and life and disability insurance
• eligible to enroll in our company 401(k) plan