Manager, Data Analytics
About the role
Your Mission
We are looking for a Data Analytics Manager to join our Data organization. This leader will oversee analytics for our Pricing & Supply teams, a highly strategic part of the business responsible for helping Engine deliver competitive pricing, strong marketplace coverage, better supplier performance, and an exceptional customer experience.
This is a high-impact leadership role for someone who enjoys operating close to the business, developing strong analysts, and turning complex marketplace and commercial questions into clear insights, scalable analytics, and better decisions. You do not need to come from a pricing or supply background, but you should be excited by the opportunity to work on problems that sit at the center of growth, margin, inventory, conversion, and customer value.
As part of Engine’s Data team, you will help shape how analytics supports a fast-growing travel technology company at scale.
What You’ll Do
- Lead, coach, and develop a team of approximately 8 data analysts supporting Pricing & Supply initiatives.
- Partner closely with leaders across Pricing, Supply, Product and Data to define analytical priorities and drive measurable business impact.
- Build a strong analytics operating model, including prioritization, stakeholder management, quality standards, reusable reporting, and scalable insight generation.
- Translate ambiguous business questions into clear analytical plans, decision frameworks, dashboards, experiments, and recommendations.
- Help the business better understand pricing performance, supplier coverage, marketplace dynamics, conversion, margin, customer behavior, and operational levers.
- Raise the bar for analytical rigor across the team, including metric definition, data storytelling, root-cause analysis, experimentation, and forecasting.
- Develop analysts into stronger business partners who can influence decisions, communicate clearly, and operate with ownership.
- Identify opportunities to improve the data foundation, partnering with data engineering and analytics engineering teams to improve tooling, data models, and self-service capabilities.