Staff Data Analyst

Vaga não está no LinkedIn

🕒 Junho 26

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $137.275 - $190.000 / ano

⏰ Tempo Integral

🔴 Especialista

📉 Analista de Dados

👻 Score fantasma 28%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Hotel Engine

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2018

🏨 Hospitalidade

📦 Logística

🛍️ Comércio Eletrônico

💰 $65.000.000 Series B em 2021-12

Hospitality • Logistics • eCommerce

A Hotel Engine é uma plataforma poderosa que simplifica as viagens de negócios ao permitir que as empresas reservem, gerenciem e economizem com facilidade em suas necessidades de viagem. A plataforma oferece acesso a mais de 750. 000 hotéis no mundo todo, possibilitando reservas sem complicações para diferentes tamanhos de grupo, de pequenas equipes a grandes eventos corporativos. Com recursos como relatórios centralizados, opções de pagamento flexíveis e suporte dedicado, a Hotel Engine tem como objetivo agilizar a experiência de viagem tanto para organizações quanto para viajantes individuais, garantindo economias significativas de tempo e dinheiro.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Competitive base pay tied to role and experience, with opportunities for bonuses, commissions, and equity. • Check out our full list at engine.com/culture.