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# Success Analytics Engineer

- **Company:** CodeRabbit Inc.
- **Location:** Boston, MA, United States
- **Experience:** Experienced
- **Salary:** $195,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Data Warehousing, Python (Programming Language), Automation of Marketing, Operational Databases, Reliability Engineering, Software Deployment, SQL Databases, Data Layers, Automation Anywhere
- **Published:** August 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=04330dfe487466c7

## About the Role

* 4+ years in data, analytics, or backend engineering, with production data warehouse experience (SQL, dbt or similar, Python)
 * You have built and operated scheduled pipelines and webhook-driven services in production
 * You have taken a product from development through production deployment and operated it live, with real users depending on it
 * You have worked directly with customer success tooling: CS platforms, CRM, marketing automation, or support systems, as a builder or a heavy operator
 * Deep experience with AI: designing AI workflows, deploying and operating different models in production, and matching the right model to each task
 * You ship on a weekly cadence and can sequence your own work against a written roadmap
 * You validate and reconcile your data before anyone has to ask

Nice to have

 * Experience with customer success, revenue, or billing data models
 * Cost and reliability engineering for AI workloads: caching, batching, structured outputs, and model routing
 * You have built internal tools that a team uses daily

## Description

You are the founding engineer for the team's data and automation tooling. You build the pipelines, scoring jobs, and services that turn product and business data into customer-facing motions, and the data layer behind the internal tools the team works from. You work directly with the Director, who is hands-on technical and builds the front end. The design work is complete: you start from a written technical spec and working prototypes, and your job is to make the system run in production., * Scheduled pipelines from billing, product telemetry, support, and CRM systems into the company's data warehouse

 * A nightly scoring job that classifies every account and detects meaningful change
 * A realtime service that triages account risk events and routes each one to automated or human follow-up within minutes
 * Campaign audience syncs with experiment controls built in
 * Digests, reporting views, and the data layer behind the team's internal console
 * AI workloads where language is the input: classification, extraction, and drafting, engineered for cost and reliability

Your first 90 days

 * Ship the first scheduled pipeline and the account scoring job, validated against existing reporting
 * Stand up the realtime triage service with alerting and runbooks
 * Support the first automated campaign cycle running on your data, with measurement controls in place


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