Data Engineer
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.
About the job
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.
Skills
SQL, Python, JavaScript, dbt, Airflow, Dagster, Data Modeling, Data Pipelines, Data Warehouse, BI Tools
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