Data Engineer, Data Product
Description
About the Role
Join a data product team at an AI company, turning complex consumer data into trusted, production-ready products. Your work will connect data engineering and applied data science, supporting products with direct commercial impact.
What You'll Do
Investigate large, unfamiliar datasets to understand their structure, relationships, coverage, and suitability for product use cases.
Design domain models and derived attributes that make messy source data useful and reliable.
Build and operate ingestion and transformation pipelines, including validation, observability, and backfills.
Find and assess new data sources, identifying how they can improve consumer data products.
Develop deep expertise in one or more data domains, such as identity, property, or consumer intent.
Work with data scientists, platform engineers, and customer-facing teams to translate ambiguous questions into scalable data products.
What We're Looking For
Typically 2 to 5 years of experience in data engineering, applied data science, or analytics engineering, with a relevant degree and strong computer science or engineering fundamentals.
Strong proficiency in Python and SQL, plus hands-on experience with large, messy, multi-source datasets, data cleaning, and domain modeling.
Experience building production data pipelines that power customer-facing data products, not only dashboards, internal reporting, or infrastructure optimization.
Experience delivering production pipelines in addition to machine learning models.
Familiarity with orchestration and transformation tools such as Dagster, Airflow, dbt, or Spark.
Experience on product or revenue-focused teams is valuable.
Compensation & Benefits
Base salary: $180,000 to $225,000 USD annually. Visa sponsorship is available.
Location
On-site in New York, New York. The role requires working from the office each day.
