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Niche Databricks specialization and seniority reduce competition despite metro location.
Databricks-specific platform expertise limits transferability across non-Databricks environments.
Explicit 8+ years, required Databricks implementation experience and platform ownership make filters highly strict.
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Own and manage the Databricks platform including administration, governance, entitlements, performance optimization, and operational management.
Build, operate, and optimize scalable, cloud-native data solutions on AWS, ensuring production readiness, reliability, security, and cost-efficiency.
Design, build, and maintain batch and streaming data pipelines with data workflow orchestration using Airflow or similar tools.
8+ years of hands-on data platform engineering experience.
Strong expertise in Databricks platform administration, entitlements/access management, governance, performance optimization, and operational management.
Experience managing Databricks workspaces, clusters, jobs, notebooks, and production Spark workloads with at least 2 end-to-end Databricks platform implementations in last 4 years.
Strong coding skills in Python, Java or similar languages, strong SQL skills, and experience with dbt for transformations and Airflow for orchestration.
Experienced in managing large-scale Databricks platform operations with demonstrated ability to optimize performance and reliability in production environments.
Skilled in building cloud-native data pipelines and streaming systems with strong engineering discipline and focus on production readiness (secure, tested, observable).
Comfortable working cross-functionally with product, analytics, and platform teams in complex, delivery-focused environments.