Whip Media is transforming the global content licensing ecosystem with a market leading enterprise software platform that centrally connects data, processes and teams throughout the digital distribution journey. Powered by predictive insights and proprietary data, we enable the world’s top entertainment organizations to efficiently distribute, control and monetize their TV and movie content to drive revenue and direct-to-consumer growth.

Whip Media Group is looking for a Senior DevOps engineer with extensive experience in data operations.  This role directly works with machine learning scientists and data engineers to support our enterprise machine learning focused applications.  This means developing and maintaining the infrastructure that powers our streaming and batch ML scoring systems as well as optimizing our ML workflow to further speed up the development lifecycle of our ML applications.  You will further iterate on our existing technology stack, which ranges from serving ML models in k8s to spark driven ETL processes.  

What will you do?

• Work with data engineers, machine learning engineers, and machine learning scientists to build and maintain enterprise quality systems core to our companies success
• Setup and maintain high levels of observability throughout our production systems
• Enable agile practices in our data pipelines and machine learning systems
• Maintain core infrastructure, including k8s clusters and various ML/Data Engineering frameworks that run on them
• Search for optimizations in our SDLC processes and enact these improvements by working with data engineers and implementing infrastructure changes
• Triage system failures, route to the appropriate team to ensure quick resolution

What do you need?

• Minimum of 10 years DevOps and/or data engineering experience
• Minimum of 3 years experience with core DevOps functions like AWS cloud infrastructure management, secrets management, CI deployment patterns
• Security aware! Must understand best practices in how to build technologies that minimize security risks to our business and our clients
• Minimum of 2 years with production kubernetes installations, experience with EKS a plus
• Minimum of 1 year having maintained core k8s DataOps packages, including istio and airflow
• Knowledge of best practices in monitoring ML services, e.g., observability, logging, metrics, etc.
• Having built and maintained reliable, secure, and observable systems with heavy focus on risk mitigation is a must for this role
• Knowledge on how to work within SOC 2 compliance structures
• Experience in monitoring core data infrastructure, e.g. Spark, a plus
• 2 years experience with infrastructure as code and extensive experience with terraform
• Knowledge of metrics and logging frameworks like prometheus, logstash, etc.
• Ability to write clean and functional python code