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Engine

Sr. Data Analyst - Finance

Posted 25 Days Ago
Easy Apply
Remote
Hiring Remotely in United States
Senior level
Easy Apply
Remote
Hiring Remotely in United States
Senior level
The Senior Data Analyst will lead metrics definition, reporting, statistical analysis, experimentation, dashboard management, and pricing analytics. The role involves building data pipelines, collaborating with data engineers on data assets and feature stores, investigating complex business questions, and translating analytical findings into strategic recommendations for product, pricing, and senior leadership. Strong SQL, statistics, econometrics, communication, and cross-functional collaboration skills are essential.
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About Engine

Engine is the AI-native platform for intelligent travel. For a decade, Engine has built the proprietary technology and supply behind modern business travel, serving over 40,000 customers and nearly 2 million travelers, along with leading travel and AI companies that build on Engine's infrastructure. One system powers business travel, group travel, human agents, and AI agents.
That work has earned Engine recognition as TravelTech's Reservation Platform of the Year (2026), a spot on Inc.'s Power Partners list (2026), and one of Built In's Best Places to Work (2020–2026).
We're looking for bold, ambitious people to help redefine how businesses manage and experience travel. Working here, you can expect exponential growth, an ambitious pace, full ownership, and high-caliber colleagues who push you to do the best work of your career. Every hire raises the bar.
Come outpace the ordinary and build the future of travel with us.

Your Mission

We’re looking for a Senior Data Analyst to build and own the data and analytics behind Engine’s internal finance function. In this role you’ll partner directly with our Head of Finance. You’ll use data, AI and automation to change how finance gets its insights: faster, more accurate and less manual. You’ll build the models, pipelines and analyses that leadership, the board and investors rely on.

What You’ll Do

  • Partner with our Head of Finance as the lead data analyst for the finance team, scoping analytical needs and turning open-ended questions into rigorous, data-driven answers.
  • Design and build the finance data layer in Snowflake, including clean, well-documented data models and pipelines that bring together ERP, billing, payroll and operational data into one trusted source of truth.
  • Use AI and automation to remove manual finance work. That includes automated reconciliations, anomaly detection, self-serve reporting and AI-assisted analysis that speeds up month-end and planning cycles.
  • Build and manage finance’s BI dashboards in Looker, giving leadership real-time visibility into revenue, margin, operating expenses and cash.
  • Use advanced SQL to explore large, complex datasets and find what’s driving revenue, margin and cost performance.
  • Apply statistical methods (e.g., regression, time-series forecasting, driver analysis) to improve forecast accuracy and support budgeting and long-range planning.
  • Go beyond surface-level numbers to explain the “why” behind financial trends, quantify opportunities and deliver clear recommendations.
  • Analyze operating expenses, headcount and vendor spend to find efficiencies and protect profitability as we scale.
  • Work with Data Engineering to set data definitions, improve data quality and build reusable data assets for advanced analytics and machine learning.
  • Turn complex analytical findings into clear, concise insights for the executive team and the board.

What We’re Looking For

  • Bachelor’s degree in Data Science, Statistics, Economics, Finance, Operations Research or a related quantitative field.
  • 5+ years of experience as a Data or Business Analyst, with a proven track record of extracting value from complex datasets, ideally in partnership with Finance or FP&A.
  • Advanced SQL skills and hands-on experience building data models and pipelines (dbt experience is a plus).
  • Strong fundamentals in statistics and econometrics, such as regression, hypothesis testing and forecasting.
  • Hands-on experience using AI tools and automation to speed up analysis and eliminate manual workflows. Python is a strong plus.
  • Solid financial literacy. You understand P&L structure, budgeting and forecasting, and how the numbers connect.
  • Excellent communication skills, including the ability to turn complex analyses into crisp narratives for senior leadership.
  • Experience with Snowflake and Looker is a plus. Familiarity with NetSuite or similar ERPs is a bonus.
  • An inquisitive mindset and a desire to dig deeper to understand the “why” behind the data.

Why Join Us

  • Join a growing, profitable and cash flow positive company.
  • Be the analytics partner to finance leadership, and directly shape budgeting, investment and operating decisions.
  • Build an AI-enabled, automated finance data foundation that scales with the company.
  • Be part of a data-driven culture that values innovation, ownership and real impact.

Compensation
Our compensation packages are based on several factors, including your experience, expertise, and location. In addition to a competitive base salary, all roles receive equity. Depending on the role, total compensation may also include an annual bonus. Your recruiter will share your complete compensation package as you move through the process.

Base Pay Range
$131,500—$154,700 USD

The Engine Edge: Perks & Compensation
We believe in rewarding great work with great benefits:

  • Compensation: Competitive base pay tied to role and experience, with equity for all employees. Some roles are also eligible for bonuses or commissions.
  • Benefits: Check out our full list at engine.com/culture 
  • Environments for Success: Different roles have different needs in terms of the environments that drive success which is why we have a hybrid-hub model. Whether you are in one of our amazing offices or fully remote, we'll make sure you have what you need to succeed.

Perks and benefits may vary based on employment type, location, and more

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