Senior Engineer, Analytics, Operations Intelligence

🕒 Maio 5

🏄 California, Colorado, +19 estados a mais – Remoto

🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🌾 Iowa – Remote 🏖️ New Jersey – Remote 🌶️ New Mexico – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $115.192 - $137.605 / ano

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

🦅 Patrocina Visto H1B

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Crisis Text Line

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2013

🤝 Sem Fins Lucrativos

🌍 Impacto Social

🧘 Bem-estar

💰 $23.800.000 Series B em 2016-06

Non-profit • Social Impact • Wellness

Crisis Text Line é uma organização global de saúde mental que oferece suporte em crise gratuito, 24/7, e confidencial via mensagens de texto. A organização sem fins lucrativos treina voluntários chamados Conselheiros de Crise para oferecer apoio emocional imediato, intervenção em crise e prevenção para questões como ideação suicida, automutilação, ansiedade, depressão e solidão. Opera como um serviço conduzido por caridade, focado em acessibilidade, impacto informado por dados e engajamento voluntário para expandir o cuidado em crises em diversos países.

Descrição

• Define and maintain performant, scalable data models in the data warehouse, with a focus on reliability, reusability, and documentation • Partner with Platform and Data Engineering to build and monitor scalable data pipelines in production • Serve as a technical authority on data modeling standards, tooling choices, and engineering best practices across the analytics function • Translate ambiguous business needs into clean, well-scoped data products — from one-time analyses to production-grade dashboards • Advocate for and drive adoption of industry best practices • Define the organization's experimentation standards: what constitutes a well-designed study, how results are interpreted, and how findings are documented and shared • Design and execute experiments — hypothesis testing, data analysis, A/B tests, quasi-experiments, and observational studies — in partnership with Operations, Marketing, and Product stakeholders • Evaluate, select, and implement the experimentation stack — prioritizing open-source and low-overhead tooling that can mature with the practice • Bring statistical rigor to ambiguous questions: help teams move from "we want to know if X works" to a study design that can actually answer that question • Communicate findings to non-technical audiences with clarity, including Senior Leadership and external partners

🎯 Requisitos

• 5+ years working with data in analytical or engineering contexts, with demonstrable depth in SQL and Python • Strong foundation in statistics and experimental design — you understand the difference between correlation and causation and know how to design for the latter • Experience designing or executing controlled experiments or quasi-experimental studies (e.g., difference-in-differences, regression discontinuity, propensity score matching) • Experience building and maintaining data models for downstream analytical use • Fluency with git and collaborative development workflows • Demonstrated ability to work cross-functionally and translate between technical and non-technical stakeholders

🏖️ Benefícios

• Comprehensive medical, dental, and vision options that prioritize accessibility and financial peace of mind • Employer-funded HSA contributions • Generous PTO, sick time, and 19 paid holidays with a winter break • 12 weeks of fully paid parental leave after 26 consecutive weeks of service • Monthly internet and mental health stipends • Annual Wellness Stipend • Home office and professional development stipends • 403(b) retirement plan with employer contribution • Sabbatical after 3 years of service