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Mid-level Databricks/Python data platform role in a metro with broad required skills attracts strong applicant density.
Data platform and Databricks skills are moderately transferable but require specific tooling and cloud experience.
Explicit 5+ years plus mandatory Databricks, Delta Lake, Python, SQL, and Terraform skills create strict screening filters.
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Design, build, and operate scalable, secure, and maintainable large-scale data platform capabilities across Azure and GCP using Databricks and associated technologies.
Engineer and automate data platform infrastructure, including workspace lifecycle management, CI/CD, Infrastructure-as-Code, and platform reliability improvements.
Collaborate with AI/ML, product, and engineering teams to enable data-driven, AI-powered product capabilities and troubleshoot complex production issues.
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, including large-scale data platforms or distributed systems in cloud environments.
Strong programming skills in Python and SQL, with experience in Databricks platform technologies (Unity Catalog, Delta Lake, Delta Sharing, Structured Streaming).
Experience with REST API development (FastAPI, Flask), Terraform, CI/CD pipelines, Docker, Kubernetes, and cloud platforms such as Azure, GCP, or AWS.
Experienced in building and operating cloud-native, enterprise-scale data platforms with strong emphasis on governance, security, and scalability.
Operates effectively in complex, ambiguous environments, driving platform engineering best practices and automation to accelerate development lifecycle.
Familiar with modern AI-assisted development tools and capable of maintaining high code quality and architectural consistency when integrating AI-generated code.