Senior Data Engineer

TripAdvisor, the world's largest travel site, is devoted to helping travelers have great experiences. We are looking for a hands-on data engineer to help us leverage the massive amount of data that we collect so that we can better understand how to guide each traveler to those experiences that are right for him/her.

TripAdvisor operates at scale with over 661 million reviews, opinions, photos, and videos reaching over 456 million unique visitors each month. We are a data driven company, and we have lots and lots of data!

This job is for a position on the Hotels Traffic Acquisition team. This team helps travelers find the best hotels for them when planning a trip. To do our job well, we need to know a lot about the traveler and the context in which our ads are being shown. This is a big data job - sifting through lots and lots of data to identify the metadata that will support an effective and enjoyable user experience. It is also a programming job - building the infrastructure needed to analyze the data as well as working directly on the code running on the live site.

We need to build features. We need to build models. We need to deploy our models to production and monitor how they do. We need to analyze the way travelers use our site/app. We need to build a platform that will let us do all these things faster to better leverage our data science and analytics teams. We need to build tools and we need to deliver functionality to our users.

This is a hands-on job for someone who wants to solve important business problems that depend on big data. The job requires both serious technical chops and effective communication skills. Sometimes you will build the solution yourself, and sometimes you will be coordinating the efforts of others, but at all times you will be expected to think creatively about solving the business problem.
What you will bring to the team:

  • Solid RDBMS operational knowledge with outstanding SQL skills
  • Ability to transform raw, noisy log level data into useful business fact tables
  • Solid database design skills
  • Computer Science expertise - algorithms, data structures, software engineering
  • Experience building data workflows and platforms, familiarity with leading libraries
  • Ability to understand and communicate business needs
  • Ability to come up to speed quickly in order to understand and coordinate the work of domain experts - in particular the ability to work effectively with the Machine Learning team.
  • Strong sense of responsibility: taking pride in your work, leveraging others, owning the problem
  • And you love, and we mean love, data

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