Data Platform Engineer – Hybrid NYC, Equity Eligible

Fonzi AI

New York (NY)

Híbrido

USD 170.000 - 240.000

Jornada completa

Hace 6 días
Sé de los primeros/as/es en solicitar esta vacante

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

Supera los filtros ATS

Descripción de la vacante

Fonzi AI, a recruiting tech company powering NYC and SF startups, is seeking data engineers to build production-grade data pipelines for AI products. You’ll own data infrastructure and models used by analysts, product and ML teams, contributing to critical data workflows.

The role focuses on the data platform for a fast-growing startup, including financial and healthcare data where correctness matters. NYC-based with hybrid or onsite work options, you’ll join a team shaping early data

Formación

  • 3+ years building data pipelines in production.
  • Proficient in SQL and Python.
  • Experience with Snowflake, BigQuery or ClickHouse.
  • Experience streaming with Kafka or Kinesis, or orchestration with Airflow or Dagster.

Responsabilidades

  • Develop data infrastructure behind AI products.
  • Work with financial and healthcare datasets where accuracy matters.
  • Help build the first data platform at a growing startup.

Conocimientos

SQL
Python
Snowflake
BigQuery
ClickHouse
Kafka
Kinesis
Airflow
Dagster
Data modeling

Herramientas

Snowflake
BigQuery
ClickHouse
Kafka
Kinesis
Airflow
Dagster

Descripción del empleo

Fonzi AI, a recruiting tech company powering NYC and SF startups, is seeking data engineers to build production-grade data pipelines for AI products. You’ll own data infrastructure and models used by analysts, product and ML teams, contributing to critical data workflows.

The role focuses on the data platform for a fast-growing startup, including financial and healthcare data where correctness matters. NYC-based with hybrid or onsite work options, you’ll join a team shaping early data

Consigue la evaluación confidencial y gratuita de tu currículum.

o arrastra y suelta tu archivo aquí