Quick overview
Job description
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.