Data engineer, data product

About the Role

Build production-ready data products from complex consumer data, working across data engineering and applied data science. Your work will help turn raw, ambiguous signals into trusted datasets that support customer-facing products and revenue-generating use cases.

What You'll Do

• Investigate unfamiliar datasets to understand their structure, coverage, relationships, and suitability for product use cases.
• Design domain models and derived attributes, then build and operate ingestion and transformation pipelines with validation, observability, and backfills.
• Evaluate new data sources and determine how they can improve consumer data products.
• Develop deep expertise in one or more data domains, such as identity, property, or consumer intent.
• Partner with data scientists, platform engineers, and customer-facing teams to turn ambiguous questions into scalable products.
• Help hire and develop a small team of data practitioners.

What We're Looking For

• Typically 2 to 5 years of experience in data engineering, applied data science, or analytics engineering, with strong Python and SQL skills.
• Hands-on experience working with large, messy, multi-source datasets, including data cleaning and domain modeling.
• Experience building production pipelines and customer-facing data products, not only dashboards, reporting, or infrastructure systems.
• Familiarity with orchestration and transformation tools such as Dagster, Airflow, or dbt; experience with Snowflake, Spark, Apache Iceberg, or Trino is relevant.
• A relevant computer science or engineering degree and strong technical fundamentals.
• Experience independently shaping ambiguous data problems, working on product or revenue-focused teams, and mentoring or developing junior teammates.
• Startup or high-growth company experience is helpful.

Compensation & Benefits

Base salary: $180,000 to $225,000 annually. Visa sponsorship is available.

Location

On-site in New York, New York.