Overview
Skills
Job Details
Title: Data Engineer (Onsite NYC)
Location: Flatiron, NYC (Onsite 5 days per week)
Compensation: $160,000 $250,000 base + 0.6% 0.9% equity
About the Role
We are seeking a Data Engineer to join a fast-scaling, venture-backed startup that is tackling massive challenges in grocery demand forecasting, supply chain optimization, and food waste reduction. This is a hands-on role where you will design, implement, and optimize data pipelines and ML systems while working closely with customers on technical integrations.
The role is 80% engineering + 20% customer-facing.
Responsibilities
Design and implement scalable data pipelines in Python/Pandas for processing large-scale customer data.
Build and maintain ETL infrastructure and optimize ML systems for demand forecasting.
Contribute to backend services powering mobile and web applications.
Collaborate directly with customers technical and operations teams to integrate systems and incorporate business logic.
Troubleshoot data ingestion, transformation, and forecasting pipeline challenges.
What We re Looking For
5+ years of experience writing data pipelines in Python and Pandas.
Proven ability to build/write DBT pipelines incorporating business logic.
Startup experience (early-stage preferred, ideally as a founder or founding engineer).
Experience collaborating directly with enterprise customers to model and implement operational data solutions.
Bachelor s degree in CS, Engineering, or STEM (exceptions for exceptional candidates).
Bonus Skills:
Familiarity with Dagster, Airflow, or Palantir Foundry.
Hands-on with Google Cloud Platform, BigQuery, Postgres, Terraform, Docker.
Tech Stack
Python, Pandas, Dagster, Airflow, PySpark, Dask, FastAPI, React, Next.js, Typescript, Google Cloud Platform, Postgres, Terraform, Docker, BigQuery
Why Apply
High-growth environment role in a startup that scaled from $50K $1M revenue in under a year.
Massive, measurable impact work on problems that save grocers millions and reduce global food waste.
Exceptional founding team YC-backed with domain expertise in grocery logistics.
Challenging problems ML, forecasting, and customer logic modeling requiring both strong coding and business understanding.
Not the Right Fit If
You are a pure data scientist focused only on analytics/experimentation.
You are only an infrastructure engineer without strong Python/Pandas experience.
You ve only worked in large tech companies without exposure to end-to-end solutions in fast-moving teams.