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Specialized Databricks skillset and mid-level metro role produce moderate competition.
Platforms and Databricks expertise transfer across industries but require specific tooling experience.
Mandatory 5+ years and specialized Databricks, cloud, and IaC requirements raise filtering rigidity.
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Design, build, and operate scalable and secure cloud-native data platform capabilities across Azure and GCP using Databricks and related technologies.
Develop and maintain platform services including data ingestion, processing, discovery, and governance tooling with automation and CI/CD best practices.
Collaborate with AI/ML, product, and engineering teams to enable data-driven and AI-powered solutions, troubleshoot production issues, and improve platform reliability.
Bachelor's or Master's degree in Computer Science, Software Engineering, or related field, or equivalent practical experience.
5+ years of relevant industry experience building and operating production software systems and large-scale data platforms or distributed systems in cloud environments.
Strong skills in Python, SQL, Databricks platform technologies (Unity Catalog, Delta Lake, Delta Sharing), REST API development, Terraform, CI/CD, Docker, Kubernetes, and cloud platforms Azure and GCP.
Experience with AI-assisted development tools and ability to maintain engineering quality when using AI-generated code.
Experienced in operating and evolving cloud-native, multi-tenant data platforms with focus on maintainability, scalability, security, and developer experience.
Skilled in infrastructure automation, governance, and platform reliability engineering with strong troubleshooting and root cause analysis capabilities.
Proficient in partnering across AI/ML and product teams to enable data and AI-driven product capabilities within an agile, collaborative environment.