Senior Engineer, Analytics, Operations Intelligence

🕒 May 5

🏄 California, Colorado, +19 more states – Remote

🏄 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

💵 $115.2k - $137.6k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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Crisis Text Line

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🤝 Non-profit

🌍 Social Impact

🧘 Wellness

💰 $23.8M Series B on 2016-06

Non-profit • Social Impact • Wellness

Crisis Text Line is a non-profit organization providing free, 24/7 support for people in crisis. Through text messaging and platforms like WhatsApp, individuals can connect with trained volunteer Crisis Counselors who offer confidential assistance. The organization helps people manage issues such as anxiety, depression, and various forms of abuse, with a mission to move individuals from a state of distress to calm. Crisis Text Line also provides volunteering opportunities and bilingual support, supporting mental health awareness and promoting empathy and resilience in communities.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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