Senior Engineer, Analytics, Operations Intelligence

This is a fully remote position, open to applicants in California, +20 more states.

📋 Description

• Develop and uphold efficient, scalable data models within the data warehouse, emphasizing reliability, reusability, and thorough documentation.

• Collaborate with Platform and Data Engineering teams to construct and oversee scalable data pipelines in a production environment.

• Act as a technical expert on data modeling standards, tooling selections, and engineering best practices throughout the analytics department.

• Convert vague business requirements into clear, well-defined data products — ranging from one-off analyses to production-ready dashboards.

• Promote and encourage the adoption of industry best practices.

• Establish the organization's experimentation standards, including criteria for well-designed studies, interpretation of results, and documentation and sharing of findings.

• Design and implement experiments — including hypothesis testing, data analysis, A/B testing, quasi-experimental studies, and observational research — in collaboration with Operations, Marketing, and Product teams.

• Assess, select, and deploy the experimentation toolkit, focusing on open-source and low-overhead tools that can evolve with the practice.

• Apply statistical rigor to ambiguous inquiries: assist teams in progressing from "we want to know if X is effective" to a study design that can provide an answer.

• Present findings to non-technical stakeholders clearly, including Senior Leadership and external partners.

⛳️ Requirements

• Over 5 years of experience working with data in analytical or engineering roles, with proven expertise in SQL and Python.

• Solid understanding of statistics and experimental design — you can distinguish between correlation and causation and know how to design studies to establish the latter.

• Background in designing or executing controlled experiments or quasi-experimental studies (e.g., difference-in-differences, regression discontinuity, propensity score matching).

• Experience in building and maintaining data models for downstream analytical purposes.

• Proficiency with git and collaborative development processes.

• Proven ability to engage cross-functionally and translate between technical and non-technical stakeholders.

🏝️ Benefits

• Comprehensive medical, dental, and vision plans that prioritize accessibility and financial peace of mind.

• Employer-funded HSA contributions.

• Generous PTO, sick leave, and 19 paid holidays, including a winter break.

• 12 weeks of fully paid parental leave after 26 consecutive weeks of service.

• Monthly stipends for internet and mental health support.

• Annual Wellness Stipend.

• Stipends for home office setup and professional development.

• 403(b) retirement plan with employer contributions.

• Sabbatical available after 3 years of service.