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Mid-level data engineer in metro with common title but niche Databricks specialty moderates competition.
Specialized Databricks and Azure skills bias fit toward cloud/data-centric employers.
Explicit 4-6 years plus mandatory Databricks, Azure, Java/Spring Boot, and API security requirements.
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Own design and development of data engineering and transformation solutions on Azure Cloud using Databricks.
Develop and integrate Databricks with enterprise applications via APIs and microservices, including automation of Databricks administration and operations.
Implement application self-healing solutions through proactive and reactive automation to ensure operational stability.
4-6 years of experience in data engineering and transformation on Cloud with 4+ years focused on Azure Data Engineering and Databricks.
Hands-on expertise with Databricks REST API, SDK (Python/Java), CLI, and strong understanding of Databricks Jobs, Clusters, Workspace, SQL Execution, Unity Catalog, and Delta Sharing APIs.
Experience in developing Java/Spring Boot microservices and knowledge of API security standards including OAuth2, IDP, JWT, Service Principals, RBAC, and Secrets Management.
Bachelor’s degree in Computer Science, Information Technology, Computer/Telecommunication Engineering or equivalent.
Deep technical expertise in Azure data engineering platforms and Databricks ecosystem with practical experience in API integration and automation.
Proven ability to build and maintain microservices using Java/Spring Boot aligned with secure API best practices.
Experienced in creating automated proactive and reactive solutions for operational resilience in cloud data environments.