Data Engineer, Data Product

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.