Senior Analytics Engineer

🔥 16 hours ago

🇺🇸 United States – Remote

💵 $190k - $250k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Eve

WebsiteLinkedInAll Job Openings

51 - 200 employees

⚖️ Legal

🤖 Artificial Intelligence

☁️ SaaS

🔥 Funding within the last year

💰 $103M Series B - Eve on 2025-09

Legal • Artificial Intelligence • SaaS

Eve is an AI-native legal software company that provides an AI operating system (EveOS) and suite of AI tools purpose-built for plaintiff law firms. Its platform automates and accelerates intake (24/7 multilingual intake and live signing), case evaluation, drafting (demand letters, complaints, discovery), medical chronologies, legal research, and litigation workflows through products like Eve Analyst, Eve Agents, Eve Auditor, Eve Research, and Atlas — a living data layer that auto-extracts and structures records. Eve emphasizes firm-wide intelligence and collaboration, integrates with existing case management systems or operates standalone, and markets itself as SOC 2 Type II certified and HIPAA-compliant. It's used by hundreds-to-thousands of plaintiff-focused firms to increase case capacity, speed up work, and improve settlements and firm performance.

📋 Description

• Own product analytics and customer success analytics domains • Build models tracking product usage, feature adoption, and launch performance, including WAU, MAU, adoption depth, and launch cohort analysis • Build customer success models for customer health, onboarding, time-to-value, renewal risk, and expansion • Own governed definitions for NRR, churn, and expansion, reconciling them with Finance reporting • Design semantic models connecting usage behavior to customer outcomes and renewal prediction • Build on source-to-staging models and conformed dimensions owned by data engineering • Work within and help shape certification frameworks and modeling standards • Partner with Product on event taxonomy and tracking plans • Instrument models with alerting for failures and drift • Maintain documentation of models, metrics, and definitions • Partner with Product and Customer Success stakeholders to turn questions into durable models • Design and review models with analysts • Build internal AI agents, data-grounded tools, and reusable skills • Build usable patterns in Omni and Hex • Scope requirements and carry projects through the full lifecycle • Report to the Head of Data Engineering

🎯 Requirements

• 5+ years in analytics engineering, owning projects end to end • Strong SQL, data modeling, and transformation, with dbt expertise: advanced modeling patterns, macros, packages, and testing • Experience building SCD tables from multiple sources • Working knowledge of Snowflake, dbt, and a semantic or BI layer such as Omni or Hex • Experience modeling product usage and event data, and the instrumentation behind it (Amplitude, Mixpanel, Pendo, or similar) • Experience modeling customer lifecycle and retention data: health scoring, renewal risk, NRR, churn, and expansion, from CS platforms and support systems • Experience designing semantic models or metric layers for human and AI consumption • Experience turning ambiguous stakeholder questions into durable models • Proficiency with AI-assisted development such as Claude Code, including agentic pipeline design and skill-based workflows • Comfort integrating tools via MCP servers • Strong communication and ability to distill technical solutions into business terms • Comfort building where the playbook doesn't exist yet • Experience in a regulated or high-sensitivity data environment (nice to have) • Experience where product usage data drove a retention or expansion motion (nice to have) • B2B SaaS experience, especially selling to small and mid-sized businesses or professional services firms (nice to have)

🏖️ Benefits

• Competitive Salary & Equity • 401(k) Program with Employer Matching • Health, Dental, Vision and Life Insurance • Short Term and Long Term Disability • Commuter Benefits (in office employees only) • Autonomous Work Environment • Workplace Setup Reimbursement • Telecomm Stipend • Flexible Time Off (FTO) + Holidays • Quarterly Team Gatherings • In office Perks (in office employees only)