Back
Mid-level generalist DevOps/data-platform role in likely metro locations with moderate brand recognition.
Skills are broadly transferable across industries but require specialized platform and data tooling knowledge.
Multiple mandatory technical skills, leadership expectations, and explicit years requirement raise screening rigor.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design, implementation, and operation of scalable, secure, and reliable data platforms and DevOps automation supporting Central Data Operations ecosystem.
Own platform services including Apache Airflow, Microsoft Fabric, Power BI, Snowflake, CI/CD pipelines, container orchestration, and developer tooling for enterprise data workflows.
Provide technical leadership, promote operational excellence, automation, and establish modern DataOps capabilities across teams including Engineering, BI, AI, and Analytics.
5+ years of hands-on experience in Data Engineering, Platform Engineering, or DevOps roles.
Strong proficiency in Python programming for automation and platform tooling.
Expertise in Apache Airflow platform design and operation, CI/CD with GitLab, Infrastructure as Code using Terraform, Linux, containers, Kubernetes, and distributed systems.
Experience with enterprise data platforms and technologies such as Docker, Helm, GitLab CI/CD, Snowflake, dbt, Microsoft Fabric, Power BI, Azure, and Oracle Analytics Cloud.
Technical leader with a strong background operating highly available and scalable data platforms and automation pipelines.
Experienced in working at the intersection of Data Engineering and DevOps with focus on platform engineering and developer experience.
Proven capability in partnering across stakeholder teams to deliver self-service data platforms and drive continuous innovation using modern DataOps practices.