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DevOps engineer | Media network

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  • At least 3 years of operations engineering experience in a team environment
  • Proficiency in writing scripts in Python and Bash
  • Extensive knowledge of Linux
  • Experience in deployment automation/configurations
  • Experience with Docker, Kubernetes
  • Experience with AWS or Google Cloud
  • Fluent English, experience working directly with US/European clients.

Do not hesitate to apply if you are missing some specific experience. We will be happy to help you with gaining one

Will be a plus:

  • Experience working with Ad-tech projects is a big plus!

What we offer:

  • Teams of people who love programming
  • Complex technical challenges with big data/AI/high load
  • Freedom to make your own engineering decisions and broad space for creativity
  • Modern technology stack to work with
  • Work remotely or from the office options on a flexible schedule
  • Long-lasting projects
  • Financial compensation for professional events and education
  • Opportunity to choose the equipment you like
  • Above-market compensation


You’ll be responsible for maintaining a cloud-deployed (AWS and Google Cloud) ad-tech project.
You’ll be defining and maintaining development environment automation for the team of developers (setting up CD/CI processes and configurations, and deployment automation), maintaining test and production environments. The area of your responsibility will be ensuring minimal cloud infrastructure costs.


The solution we are working on is a complex distributed software mechanism controlling advertising campaigns running on leading entertainment media products like Rovio, EA, Spil Games, and many other gaming, entertainment, and lifestyle sites. The system enables the biggest advertisers across the world to run highly targeted ads, personalize ad communication, predict user consumption behavior, make deep multi-dimensional analytics. We serve over 2 billion ads per month across 400 publisher sites.

Tech stack includes Java, Scala, Typescript, AWS, GCP, Docker, MongoDB, Google BigQuery


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