Senior Analytics Engineer
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Job Description
Senior Analytics Engineer governing product usage, customer health, retention, and expansion metrics. Building analytics models and AI-enabled data tools for Eve’s AI legal technology platform.
Responsibilities:
- 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)
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