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Metro location, mid-level experience, and general data role amplify competition but specialized Databricks/Azure skills moderate density.
Data platform skills (Databricks, Spark, Delta Lake, Azure) are reasonably transferable across industries, not narrowly specialized.
Explicit 5+ years requirement plus mandatory Databricks, Azure, Spark, and Terraform experience increases filter strictness.
Design, develop, and maintain Columbia Sportswear's enterprise data platform built on Azure, Databricks, and Delta Lake at a global scale.
Build scalable data pipelines, frameworks, and platform tooling adhering to established architecture, ensuring high-quality reporting and performance optimization.
Collaborate across global IT teams and participate in agile scrum ceremonies; provide mentorship and support production through on-call rotations.
Minimum 5 years experience in data engineering or data platform roles, with at least 3 years in cloud environments (Azure preferred).
Hands-on experience with Apache Spark, PySpark, Databricks, Delta Lake, and strong SQL/query optimization skills.
Bachelor's degree in Computer Science, Engineering, or equivalent experience.
Familiarity with Azure Data Factory (or equivalent pipeline tooling), infrastructure as code (Terraform or equivalent), and good communication skills.
Proven ability to architect and implement cloud-based data platforms using modern tools and security best practices (Azure Key Vault, Unity Catalog).
Experienced working effectively in distributed global teams within agile environments, balancing autonomy with collaboration.
Capable of leading technical strategy and mentoring junior engineers while managing integration patterns across data ingestion, transformation, and consumption layers.