TripAdvisor, the world’s largest travel site, operates at scale with over 760 million reviews, opinions, photos, and videos reaching over 490 million unique visitors each month.  We are a data driven company, and we have lots and lots of data! 

The Data Warehouse team at TripAdvisor is responsible for maintaining the petabyte-scale data lake, and we are looking for the right dev-ops engineer to help us take it to the next level. 

The ideal candidate will have hands-on and operational experience with Big Data technology. Our technology stack is a hybrid of open-source Hadoop/CDH cloud and house-built distributed platforms to help drive the analytics of the company. We’re also increasing our footprint on AWS and designing new platforms that integrate our on-prem environments with those. A successful engineer will need to be able to solve problems in a complex and distributed environment, as well as communicate and interact with other teams and engineers. 

What you will be doing:

  • Writing code! This is an engineering role, after all.
  • Working with a team of engineers to identify and improve upon the operational deficiencies of modern Big Data systems. 
  • Using your expertise to help scale a multi-datacenter analytics platform.
  • Jumping head-first into complex code to implement solutions to operational shortcomings.
  • Leading engineering best practices, especially those surrounding build systems and development environments.
  • Moving quickly to create today’s solutions. 

What you will bring to the team:

  • 5+ years of Dev-Ops experience
  • 5+ years of in-depth technical experience with Big Data technologies such as Hadoop, Hive, Presto, Kafka, or Spark
  • Proven experience with Amazon Web Services technology, including S3, EMR, Glue, and Athena
  • Familiarity with the Linux operating system and Bash shell
  • Familiarity with build systems such as Jenkins
  • General software engineering expertise; Most of our codebase is in Java, but we have a lot of Kotlin, Python, and Shell code as well. 
  • Ability to communicate effectively in an operations environment
  • Willingness to "get your hands dirty" with Big Data



 

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