Senior Analytics Engineer

Hotel Engine is the world’s largest Lodging Performance Network, established to create a richer, more rewarding business travel experience by connecting a global network of businesses and lodging partners. Our innovative travel-tech company is on an incredible growth trajectory and will continue to build on our strong foundations by bringing our customer obsession, data-driven problem-solving, and bias for action into every decision we make.

Following a 2021 series B funding round at a $1.3 billion valuation, we achieved remarkable growth in 2022. We expect 2023 to be our best year yet.

Working hard behind the scenes building and supporting our platform are exceptional people–from our large engineering and product teams to our fast-growing sales, supplier, and member support orgs, to our data, marketing, and operations teams.

We value our individuality, and we also understand that together, we thrive. Most importantly, we know we’re not for everyone! We’re focused on finding the right people who are energized by our culture, with diverse experiences and backgrounds that will help us unlock our full potential. Complacency doesn’t live here. We’ve built a team of world-class people who really want to work with other world-class people. Click here to view our DNA, and if you like what you see, please, read on!

We are looking for a Senior Analytics Engineer to join our Data Science & Engineering team and partner with stakeholders across the organization to ensure we efficiently acquire, store, and organize our data, make it readily available across the organization, and continue to establish a robust and efficient process to create, monitor, and share key business metrics and analytics to inform product and business decision. You will be responsible for our entire analytics infrastructure and will lead the work on the architecture, building, and operation of the various components of this infrastructure. The individual must be highly motivated, a self-starter with a strong track record of achievements, and both an obsession for rigorous work and bias for action.

If you are passionate about travel, about working on both strategic project and hands-on implementation, and relate to our vision and DNA, please apply.

Here’s what you’ll do:

Design, build and continuously improve upon core data pipelines and data models
Manage our Snowflake data warehouse, and associated pipeline (leveraging dbt, Airflow)
Work closely with our product and development teams to design and implement foundational data tables, logs and assets
Identify novel sources of relevant data (internal and external) and integrate them into our data warehouse
Manage and expand our rate shopping and data scraping infrastructure
Manage our end-to-end BI stack and enable self-service generation of insights through reporting and alerting
Improve key business processes through automation
Maintain and improve our data catalog

Here’s what we’re looking for:

Bachelor’s degree in Computer Science or related quantitative field
3+ years of relevant work experience as data engineer or analytics engineer with a track record of building and managing analytics infrastructure
Experience building complex SQL queries including on large and complex datasets, and on optimization of query performance
Experience in Python
Experience in dbt or a similar data orchestration tool
Experience in Apache Airflow or a similar workflow management tool
Experience in Snowflake or a similar cloud data warehouse
Experience in Looker or a similar BI tool
Excellent communication skills with the ability to distill complex issues and processes

Cash Compensation:

In addition to a compelling equity package, a reasonable expectation for total cash compensation for this role is between $130,000 - $170,000/year (made up of base plus bonus). Final offer amounts are determined by multiple factors, including prior experience, expertise, and may vary from the amount above.

Remote opportunities:

This role is eligible for remote work, and you can work from anywhere in the U.S.

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