Engine Sr. Data Analyst - Finance at Engine builds and owns data and analytics for the internal finance function. The role involves partnering with finance leadership to automate processes and deliver insights using advanced data techniques.
Responsibilities
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.
Qualification
Bachelor’s degree in Data ScienceSolid financial literacyExcellent communication skills
Required
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.
