Data Engineer

What you'll do

• Own data ingestion, modeling, and transformation pipelines, extending the data asset and improving reliability, speed, and quality.
• Expand external system connections and scale data workflows with data scientists for production analytics and machine learning use cases.
• Create programmatic interfaces for AI-driven applications to query and consume data.

What they ask for

• Hands-on experience building and owning end-to-end ingestion pipelines for large, messy, multi-source data.
• Experience building data pipelines for machine learning or analytics use cases; modeling-, MLOps-, or LLM-infrastructure-only backgrounds are not a fit.
• Record of architecting and running reliable, high-volume data systems.
• Proficiency with workflow orchestration and transformation tools, plus experience at a startup, high-engineering-bar company, or data infrastructure vendor, and comfort with cloud data warehouse analytics engineering and modeling.

Nice to have

• Degree from a highly ranked computer science program.
• Experience building infrastructure for AI and machine learning applications, such as retrieval services.

Pay

USD 200,000 to 250,000 per year (base salary)

Tools

Airflow, Dagster, Prefect, dbt, SQLMesh

AI focus

Build data pipelines for machine learning and create interfaces for AI-driven applications to query and consume data; supporting AI/ML infrastructure such as retrieval services is a plus.