Data Engineer - Remote

Role overview

Join Artisan as the first data-focused Data Engineer. You will own end-to-end data engineering for a system containing hundreds of millions of leads, and build real-time intent signals derived from lead data fields to support product and machine learning.

Responsibilities

• Design, build, and maintain scalable data pipelines for structured and unstructured data.
• Ingest data from third-party APIs, internal systems, and customer datasets.
• Develop and optimize data models, schemas, and storage solutions for ML and product performance.
• Work with ML engineers to create model-ready datasets, embeddings, feature stores, and evaluation data.
• Implement data quality monitoring, validation, and observability to ensure integrity.
• Contribute to early architecture, infrastructure design, and data governance.
• Support product engineering by enabling data needed for complex downstream capabilities.

Requirements

• 3+ years as a Data Engineer.
• Proficiency in Python and SQL.
• Experience with modern data tooling such as dbt, Airflow, Dagster, or similar.
• Strong production experience with ETL/ELT pipelines.
• Hands-on experience with cloud platforms (AWS, GCP, or Azure).
• Familiarity with data lakes, data warehouses, and vector databases.
• Experience integrating APIs and working with semi-structured data (e.g., JSON, logs, event streams).
• Strong understanding of data modeling and schema design/optimization.

Nice to have

• Experience with LLMs, embeddings, or ML training pipelines.
• Prior startup experience.

Location / work mode

• Remote (also possible to work from San Francisco or New York offices).