Data Platform Engineer

Experience with our stack is a bonus, but similar experience working on problems at our scale is required:

dbt
Temporal
dltHub
Duckdb / Motherduck
Dagster
What you'll do
You own the data platform end to end — ingestion, transformation, orchestration, and the reliability of all three.

As importantly, you’ll need to further develop our existing AI agents that write, build, and test new integrations end-to-end. Automating your job is the only way you will scale it.

Beyond that you’ll:

Own data platform reliability as we scale

Optimize ingestion pipelines for low-latency data availability, ensuring consistent performance during peak seasonal surges.

Build our data transformation layer so Hazel has clean, predictable data to work with.

Automate your own job, especially the data integrations and transformations

Ship new source integrations end to end

Who we're looking for
4+ years building production data infrastructure, with real ownership of a warehouse someone else depended on.

Deep understanding of dbt and SQL. You have opinions about grain, incrementality, and data modeling.

Strong Python. Our ingestion layer is code you'll be writing, not a UI you'll be clicking.

You've owned an orchestrator in production — Dagster, Airflow, Temporal, Prefect, whatever es.

AI-native in practice. You use coding agents to do the work of a much larger team, and you can tell us where they helped and where they made things worse.

You write documentation well, because here it's a feature.

Comfortable being the only person who does this job, and equally comfortable making sure that stops being true.

Nice to have: Experience with open table formats, e-commerce/DTC data (Shopify, Klaviyo, Amazon SP-API, ad platforms), and designing multi-tenant warehouses.

Comp & benefits
$155–200K base

0.3–0.5% equity

Top-tier health, dental, vision

401(k)

Unlimited PTO

Hybrid in NYC

How we hire
15-min intro

Founder call

Systems design and case study

Onsite