Success Analytics Engineer

CodeRabbit

$156K — $195K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years in data, analytics, or backend engineering, with production data warehouse experience (SQL, dbt or similar, Python)
  • Experience building and operating scheduled pipelines and webhook-driven services in production
  • Demonstrated ability to take a product from development through production deployment and live operation
  • Experience working directly with customer success tooling, CRM, or marketing automation systems
  • Deep experience designing and deploying AI workflows and models in production
  • Able to ship on a weekly cadence and manage work against a roadmap
  • Proficient in validating and reconciling data proactively

Responsibilities

  • Build scheduled pipelines from billing, product telemetry, and CRM into the data warehouse
  • Create a nightly scoring job to classify accounts and detect changes
  • Develop a real-time service for triaging account risk events
  • Implement campaign audience syncs with built-in experiment controls
  • Design reporting views and the data layer behind internal tools
  • Engineer AI workloads that utilize language classification and data extraction

Benefits

  • Opportunities for professional development
  • Flexible work hours and potential remote work options
  • Collaborative work culture focused on measurable results
  • Hands-on experience with cutting-edge AI and data technologies
  • Direct mentorship from a hands-on technical director
Full Job Description
The role

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.

What you'll build
  • 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


What you'll bring
  • 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


How we work

The team runs on measured results. Campaigns ship with control groups, numbers are labeled by source, and every report traces to rules anyone can audit.

OTE for this role is up to $195K. Actual salary will be based on job-related skills, experience, and location.

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