About the role

You will own the dbt codebase, manage data ingestion reliability, and build certified data marts to support growth and finance teams. Additionally, you will troubleshoot pipeline breakages and collaborate with product engineers on event instrumentation.

What they look for

Dbt Snowflake Airflow Airbyte SQL PostHog Stripe Metronome Data modeling Pipeline debugging Event instrumentation Git CI/CD Data warehousing Analytics engineering

Requirements

The ideal candidate is a senior analytics or data engineer with extensive experience in dbt, cloud warehouses, and production-grade orchestration. You must be comfortable working as a contractor, possess strong software engineering practices, and have experience with billing and event analytics.

Full description

The Role

Comfy's analytics stack is young and moving fast: Snowflake and dbt, Airbyte and Airflow, PostHog events, Stripe and Metronome billing, Hex on top. It was stood up quickly by our backend team and interim help, and it now powers real decisions — revenue pacing, activation funnels, finance close, enterprise deals. We need immediate support on growth analytics and this role is the engineering muscle behind that: keep the data layer true, ship the models, troubleshoot.

This is a hands-on contract role with real authority. You'll own the dbt project day to day, be the person who reviews and merges data-platform pull requests, and be the reason pipeline breakages get caught in hours instead of weeks.

What You'll Do

Own the dbt codebase: model, test, review, and merge — clear the PR queue and keep main green

Own ingestion reliability across Airbyte/Airflow jobs (product DB, PostHog, Stripe, Metronome, HubSpot), with monitors and alerts so silent failures stop happening

Turn hand-built SQL into tested, scheduled dbt models — starting with finance's views, so monthly close runs off the warehouse, not heroics

Build and certify the marts behind our dashboards: revenue and bookings, activation, team plans and workspaces, credit usage

QA and extend event instrumentation with product engineers: tracking plans, event naming, identity stitching, catching the funnel events that don't fire

Unblock the people waiting on data: growth's dashboard build, finance's close, enterprise's usage-analytics features

You Might Be a Fit If You

Are a senior analytics or data engineer for whom dbt + a cloud warehouse (we're on Snowflake) is home turf

Ship like a software engineer: git-native, strong PR reviewer, tests and CI by default — comfortable being the merge authority on a shared repo

Have run orchestration and ingestion in production (Airflow, Airbyte or Fivetran) and can debug a pipeline end to end, from source API to dashboard

Have modeled billing and subscription data before — Stripe required-level familiarity; usage-based billing (credits, metering, Metronome-style) is a strong plus

Know event analytics (PostHog, Segment, or GA4): tracking plans, event QA, identity resolution

Work at contractor pace: scoped outcomes, fast clock, crisp async communication with a small intense team

Bonus Points

You've been the data platform person at a PLG SaaS company

Hex (or similar notebook-BI), Datadog monitors, Terraform

You know ComfyUI, or care about AI creative tools

(Contract) Analytics Engineer — Data Platform