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.