At EF World Journeys, we believe that the best way to learn about the world is to experience it, and we strive to help as many people as possible share that experience. EF Go Ahead Tours, EF Ultimate Break and EF Adventures are divisions of EF World Journeys, and we make world travel easy. We want to empower travelers of all ages to get out there and experience something new on our guided tours. If you share this passion for opening the world, come work with us!
On the WoJo Engineering team you'll join a group of engineers, product professionals, analysts, and UX/UI designers who build the applications and systems that make travel happen. We power every step of the customer journey, from the e-commerce experience on the web to the mobile app that enhances the trip itself, and we power the internal tools our teams use to serve those customers. As a Data Engineer, you'll help build and operate the data platform our teams rely on, including the data foundations behind our growing AI and machine learning work.
What you’ll do
- Translate ambiguous business questions into trusted data products: modeled datasets, metric definitions, and documentation that analysts, product, and business partners can rely on.
- Design and evolve our semantic layer so the same definitions power dashboards, self-serve analysis, and LLM-driven analytics.
- Build and own dbt models that turn raw data into well-tested analytical datasets, with business logic defined once and reused across brands.
- Model Google Analytics (GA4) and our other digital analytics into datasets marketing and product can trust: sessions, events, and on-site behavior, joined to how travelers discover, consider, and book a tour.
- Partner with analysts and stakeholders to shape the question before you build. Bring the dataset that will change a decision, and say so when a request will not.
- Activate trusted data into the tools the business already runs on, including marketing, CRM, and advertising: reverse ETL (Hightouch) and the product catalogs behind our advertising and personalization channels.
- Turn recurring questions into something people can answer themselves: clear metrics, semantic models, and lightweight AI-assisted workflows, with you still accountable for the definition and the result.
- Build data quality into everything you ship: automated tests, monitoring, and explicit ownership of the numbers.
- Set the modeling and review bar for your domain, and mentor engineers and analysts who are building toward it.
- Contribute to the direction of our analytical layer: where we invest in shared models, where we enable self-serve, and which questions are worth a durable data product.
How you work
- You take ownership, from an unclear problem through a trusted data product in production.
- You collaborate as a partner. You join discovery early, shape scope with analysts, product, and the business, and give and receive candid feedback.
- You care about maintainability: clean models, thoughtful reviews, and documentation others can rely on.
- You balance pragmatism with quality, knowing when a directional dataset should ship and when the definition needs to be right first.
- You use AI tools to work smarter, and you build the definitions and semantic foundations that let teammates and agents use them well.
What you'll bring
- Experience owning analytical data products that other people use to make decisions (typically 5+ years in analytics engineering, analytics, or a closely related data role).
- Strong SQL and hands-on experience modeling in a cloud data warehouse (Snowflake preferred).
- Hands-on experience with dbt (dbt Core and/or dbt Cloud), including models, tests, and documentation other people extend.
- Experience defining shared metrics or a semantic layer that reporting, self-serve, or AI tools depend on.
- A track record of partnering with analysts and business stakeholders, including reframing a request around the decision it is meant to inform.
- Experience mentoring, reviewing, or raising the bar for other engineers or analysts.
- Working proficiency in Python for data tooling and automation.
- Bonus: reverse ETL / data activation (Hightouch), or product data that powers marketing and advertising.
- Bonus: semantic layers or metric layers used by LLM-driven analytics or self-serve tools.
- Bonus: digital analytics event data, especially Google Analytics (GA4): sessions, events, and models that connect web behavior to business outcomes.
- Bonus: measurement for experimentation, lifecycle, or marketing attribution.
You can expect:
The opportunity to travel on one of our tours every year at no cost and without using your paid vacation.
Four weeks of paid vacation and twelve paid holidays.
Professional growth opportunities, including monthly trainings, workshops, and talks with global leaders and experts.
A 25% company match on your 401(k).
Medical, dental, and vision coverage, along with life and disability insurance.
Paid international business travel.
Wellness benefits and an annual fitness reimbursement.
EF program discounts, including travel, language schools, childcare, and more.
Dependent-care, healthcare, and commuter flexible spending accounts.
Discounts at local venues and businesses.
Compensation range for the Senior Analytics Engineer role is $135,000-$170,000, based on experience.