Data Engineer, Data Product

True; New York (NY); On-site; USD 180,000 - 225,000; Full time

Job summary

Unknown company is seeking a data engineer to build production-ready data products from complex consumer data, collaborating with data science and platform teams in New York.

You will design domain models, build robust ingestion and transformation pipelines, and backfill data while ensuring validation and observability. The role emphasizes ownership of data products and mentoring junior teammates in a fast-growing environment.

Qualifications

• 2–5 years in data engineering, data science, or analytics engineering.
• Hands-on with large, messy multi-source datasets and data cleaning.
• Experience building production pipelines and customer-facing data products.
• Familiarity with orchestration/transform tools and modern data platforms.
• Degree in CS/engineering with strong technical fundamentals.
• Experience mentoring junior teammates and working in startups or high-growth teams.

Responsibilities

• Investigate unfamiliar datasets to understand structure and coverage.
• Design domain models and derived attributes for product use cases.
• Build ingestion/transformation pipelines with validation and backfills.
• Evaluate new data sources to improve consumer data products.
• Develop deep expertise in data domains like identity, property, or consumer intent.
• Partner with data scientists and platform engineers to build scalable products.

Skills

Python

SQL

Data pipelines

Mentoring

Education

CS or Engineering degree

Tools

Dagster

Airflow

dbt

Snowflake

Spark

Apache Iceberg

Trino

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.