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Mid-level metro role with common Databricks/Azure skills and moderate brand exposure, yielding medium competition.
Databricks, Azure, and Spark skills transfer across industries, but enterprise lakehouse governance adds moderate sensitivity.
Explicit 5+ years and Databricks/Azure/Spark/Terraform requirements make shortlisting strict.
Design, develop, test, maintain, and support Columbia Sportswear's Enterprise Data Platform built on Azure, Databricks, and Delta Lake at global scale.
Develop and maintain data pipelines, platform tooling, and scalable data platforms using Databricks, Data Lake, Data Factory, and Data Warehouse technologies.
Participate in agile scrum team ceremonies, provide technical and architectural design, mentor junior engineers, and support on-call production coverage.
5+ years of experience in data engineering or data platform roles, with at least 3 years in a cloud environment (Azure preferred).
Hands-on experience with Apache Spark, PySpark, strong SQL skills with query optimization expertise.
Experience with Databricks, Delta Lake, Azure Data Factory, Azure Key Vault, and CI/CD pipelines using GitHub and Terraform.
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience; familiarity with enterprise data governance and infrastructure-as-code tooling.
Experienced in cloud data platform architecture, especially Azure-based big data and lakehouse implementations at enterprise scale.
Comfortable working autonomously and collaboratively across distributed, cross-timezone global teams within an agile environment.
Able to lead technical design discussions, mentor junior engineers, and contribute to continuous improvement of data platform and governance.