Senior Data Platform Engineer — AI-Driven, Low-Latency

Hazel; New York (NY); Hybrid; USD 155,000 - 200,000; Full time

Benefits offered by this job

Health, dental, vision

401(k)

Unlimited PTO

Equity

Hybrid in NYC

Job summary

Hazel is seeking a data platform engineer to own the end-to-end data platform, from ingestion to transformation and orchestration, ensuring reliability and low-latency access for a live data warehouse used by consumer brands.

You will advance our AI-native data layer, build new source integrations, and automate complex data workflows with dbt, SQL, Python, and Dagster. Hybrid in NYC with strong compensation and equity.

Qualifications

• 4+ years building production data infrastructure with ownership of a warehouse.
• Deep understanding of dbt and SQL with opinions on grain, incrementality, and data modeling.
• Strong Python for ingestion layer development.
• You have owned an orchestrator in production (Dagster, Airflow, Temporal, Prefect).
• AI-native in practice, using coding agents to automate work.
• You write documentation well, because here it's a feature.
• Comfortable being the only person who does this job, and helping scale it.

Responsibilities

• Own data platform reliability as we scale.
• Optimize ingestion pipelines for low-latency data availability during peak loads.
• Build the data transformation layer to ensure clean, predictable data.
• Automate data integrations and transformations for efficiency.
• Ship new source integrations end to end.

Skills

dbt

SQL

Python

Dagster

Airflow

Temporal

Tools

Dagster

Airflow

Temporal

Job description

Hazel is seeking a data platform engineer to own the end-to-end data platform, from ingestion to transformation and orchestration, ensuring reliability and low-latency access for a live data warehouse used by consumer brands.

You will advance our AI-native data layer, build new source integrations, and automate complex data workflows with dbt, SQL, Python, and Dagster. Hybrid in NYC with strong compensation and equity.