Staff Data Analyst, Engine X

Engine is transforming business travel into something personalized and rewarding. The Staff Data Analyst will serve as the analytical execution layer for Engine X, ensuring accurate analytical output and reliable dashboards to support product managers, finance, and leadership in decision-making.

Responsibilities:

• Build, maintain, and improve Engine X's core performance dashboards; covering card activation rates, spend volume, gross booking value, rewards utilization, spend category breakdowns, and cardholder retention
• Track and report on key Engine X metrics on a regular cadence, ensuring stakeholders across product, finance, and leadership have accurate and timely visibility into card performance
• Investigate data anomalies and surface findings clearly; when a metric moves unexpectedly, you diagnose it, document what you found, and communicate it before it becomes a question someone else is asking
• Write and maintain complex SQL queries to extract, clean, and aggregate data from Snowflake across card transaction logs, booking activity, rewards ledger data, and cardholder activation events
• Build and document reusable data models and reporting assets that the team can rely on — well-structured, well-named, and built to last beyond the person who created them
• Support A/B tests and product experiments by setting up the analytical framework, pulling results accurately, and presenting findings in a format that informs a clear decision
• Partner with senior analysts and product managers to scope analytical requests, understand what's being asked, and deliver work that's precise, complete, and ready to act on
• Collaborate with analytics engineering and data engineering to flag data quality issues, validate pipeline outputs, and ensure the underlying data powering Engine X reporting is reliable
• Develop and maintain clear documentation for the metrics and models you own, definitions, logic, known limitations, and refresh cadences, so the team always knows what the numbers mean

Requirements:

• Bachelor's degree in Data, Economics, Statistics, Computer Science, Finance, or a related quantitative field
• 7+ years of relevant experience in data analytics or a closely related analytical function, with demonstrated ability to produce clean, accurate, and well-structured analytical work
• Solid SQL skills with experience writing complex queries — joins, aggregations, window functions — on large datasets; hands-on experience with Snowflake
• Experience building and maintaining dashboards or reporting frameworks using HEX, Looker, Tableau, or a comparable BI tool
• Attention to detail and a strong sense of ownership over the accuracy of your own work — you check your numbers, document your logic, and flag issues before they propagate
• Clear written and verbal communication skills; able to present findings in a structured, easy-to-interpret format for non-technical stakeholders
• Familiarity with A/B testing and experiment analysis — comfortable pulling results and applying basic statistical reasoning to interpret them correctly
• Curiosity about the product and business context behind the data — you want to understand what you're measuring and why it matters, not just how to pull it
• Experience in fintech, payments, card products, or financial services analytics is a plus
• Familiarity with dbt or experience working alongside analytics engineering teams to understand and leverage data models is a plus