Staff Data Analyst, Growth

Engine

21h•Hybrid

About The Position

Engine is transforming business travel by creating a personalized, rewarding, and simple experience. They are building a platform that integrates corporate travel, a charge card, and modern spend management. Engine is experiencing rapid growth, is cash flow positive, and is backed by major investors. They have been recognized as a fast-growing travel and fintech platform. This role is for a Staff Growth Data Analyst to join the Data organization, supporting Marketing, Growth, and Product teams. The analyst will focus on understanding customer behavior throughout their journey on the platform (discovery, evaluation, activation, conversion, retention, expansion) and how marketing investments, product-led growth (PLG) strategies, and experimentation impact key business metrics like sign-ups, revenue, and customer value. This is a high-impact position requiring deep expertise in growth analytics, marketing analytics, PLG, and experimentation. The role involves close collaboration with various departments to measure performance, optimize acquisition and conversion, evaluate PLG initiatives, and identify growth drivers. The ideal candidate is analytical, technically proficient, comfortable with ambiguity, skilled in SQL and data modeling, capable of building reporting frameworks, designing and analyzing experiments, and translating complex data into actionable recommendations for business leaders.

Requirements

7+ years of experience in growth analytics, marketing analytics, product analytics, business analytics, data science, or a related analytical role.
Strong experience supporting Marketing, Growth, Acquisition, Revenue, or Product teams in a high-growth business environment.
Experience with product-led growth motions, including self-serve funnels, activation, onboarding, free-to-paid conversion, product-qualified leads, retention, and expansion.
Deep hands-on experience with experimentation, including A/B testing, experiment design, statistical analysis, incrementality measurement, funnel experimentation, and translating results into business recommendations.
Hands-on experience with attribution modeling, campaign measurement, UTM tracking, conversion analysis, and marketing performance metrics such as CAC, LTV, ROAS, conversion rate, churn, retention, and payback period.
Strong SQL skills and experience working with large, complex datasets, ideally in Snowflake or a similar cloud data warehouse.
Experience with BI tools such as Looker, Tableau, Power BI, or similar platforms.
Strong business judgment, communication skills, and ability to connect analytical work to customer growth, revenue, margin, efficiency, retention, and long-term business performance.
Experience working cross-functionally with marketing, data, product, engineering, and finance teams.

Nice To Haves

Experience with Marketing Mix Modeling / Media Mix Modeling.
Experience with marketing, product analytics, and experimentation platforms such as Google Analytics, Amplitude, Mixpanel, Optimizely, Statsig, Eppo, LaunchDarkly, Google Ads, Meta Ads Manager, or similar tools.
Experience with dbt, modern analytics engineering workflows, and cloud data environments.
Experience with Python or R for advanced analysis, modeling, automation, experimentation analysis, or statistical work.
Experience with customer segmentation, cohort analysis, LTV modeling, propensity modeling, churn modeling, causal inference, lift studies, or product-qualified lead scoring.
Experience working in a PLG, self-serve SaaS, marketplace, travel, fintech, e-commerce, or other high-transaction-volume growth environment.

Responsibilities

Lead analytics across marketing acquisition, product-led growth, lifecycle growth, and channel performance, spanning paid, organic, lifecycle, partnership, affiliate, referral, and in-product channels.
Own analysis of the full growth funnel, including acquisition, activation, onboarding, conversion, retention, monetization, expansion, and long-term customer value.
Develop and improve attribution, campaign measurement, and marketing efficiency frameworks to help the business understand what is driving sign-ups, revenue, CAC, ROAS, LTV, and payback.
Lead experimentation analytics across the growth funnel, including A/B tests, incrementality tests, onboarding experiments, landing page tests, lifecycle experiments, pricing/packaging tests, and in-product conversion tests.
Design and evaluate experiments end to end, including hypothesis development, metric selection, test sizing, statistical interpretation, readouts, and rollout recommendations.
Build dashboards, reporting frameworks, and analytical models that give teams clear visibility into performance across campaigns, channels, segments, cohorts, funnels, and experiments.
Analyze customer journeys using campaign data, UTM parameters, product usage data, conversion events, lifecycle touchpoints, and marketing schemas to improve tracking quality and uncover growth opportunities.
Develop or support advanced analyses such as LTV modeling, customer segmentation, propensity modeling, churn analysis, product-qualified lead scoring, and upsell/cross-sell opportunity analysis.
Partner with Data Engineering and Analytics Engineering to improve data quality, event instrumentation, marketing/product data models, and self-service reporting infrastructure.
Communicate insights, tradeoffs, experiment results, and recommendations clearly to Marketing, Growth, Product, Finance, and executive stakeholders.