Builds and scales data pipelines, models, and integrations to provide real-time insights for product, engineering, finance, and GTM teams. Requires 4+ years experience with SQL, Python/JavaScript, dbt/Airflow, and data architecture.
Salary not listed
On-site4+ YOEData Engineering
About the role
Responsibilities
Build and refine the data models and warehouse architecture that serve as the backbone for product analytics, usage reporting, and business operations.
Design, operate, and scale the pipelines that move, transform, and validate data across internal and external systems.
Create the integrations that bring third-party and operational data into a unified, trusted environment.
Own the entire reporting surface, from core datasets and dashboards to the metrics leadership uses to steer the company.
Drive data quality, observability, governance, and documentation while helping teams adopt a self-serve analytics culture.
Qualifications
4+ years of experience in data engineering or a full-stack data role with deep expertise in SQL and strong proficiency in JavaScript or Python.
Hands-on experience with data modeling, warehouse architecture, and BI-oriented schema design, along with operational familiarity using tools like dbt, Airflow, or Dagster.
Experience supporting or building business intelligence environments.
Strong statistical intuition and experience running or supporting experimentation frameworks.
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