Job Description
📋 Description Build infrastructure for ingesting, cleaning, transforming, and merging data. Design semantic models and ontology layers for data meaning and context. Design and operate reliable DAG-based data workflows. Build data pipelines and transformation systems from scratch. Evaluate databases, storage tech, and orchestration tooling per product needs. Make large datasets performant and accessible to AI agents, analytics, and BI. 🎯 Requirements 5+ years of professional data engineering or related software engineering. Experience building a data platform, data warehouse, or major pipeline from scratch. Product company experience or owning an internal product. Strong production-level programming, particularly Python or another backend language. Hands-on with ETL/ELT frameworks such as dbt, Dagster, or similar. Experience deploying and operating DAG-based orchestrators such as Airflow. 🎁 Benefits Generous stock options. Visa sponsorship and relocation support for qualifying international candidates. Foundational role with direct influence over architecture and product direction. Opportunity to build a new category of data infrastructure for AI agents. Highly collaborative environment with a strong founding team.
