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Tier-1 brand, metro location, and broad multi-cloud/data requirements increase qualified applicant density.
Cloud data platform leadership skills are broadly transferable across industries, making background fit moderately flexible.
Mandatory 12+ years and specific cloud, data platform, and DevOps skills make filters highly selective.
Drive design and implementation of modern, scalable, secure data platforms on AWS and Azure using Lakehouse architectures and services like S3, Azure Data Lake, Databricks.
Lead and mentor a global team of data engineers and platform engineers, establishing platform strategy, governance, and best practices.
Own DevOps initiatives including CI/CD pipelines, infrastructure-as-code, cloud security best practices, and performance optimization across multi-cloud environments.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
12+ years of experience in cloud and data platform architecture, DevOps, or related technical roles.
Hands-on expertise with AWS and Azure services (e.g., S3, Glue, Lake Formation, Azure Data Factory, Synapse, Databricks) and experience with DevOps pipelines using Terraform, CloudFormation, ARM templates, etc.
Proven leadership experience with cross-functional teams and ability to drive outcomes.
Experienced in architecting and delivering medallion Lakehouse architectures using AWS/Azure data platforms in production.
Strong in cloud security architecture, data governance frameworks, and cloud cost optimization strategies.
Comfortable leading technical teams in Agile/Scrum environments, with a hands-on approach to cloud-native solutions and DevOps automation.