We’re looking for a Senior Data Engineer to join our Data Engineering team, which makes Clipboard’s data and knowledge infrastructure reliable and well-governed for everyone who makes decisions with it, human analysts and AI agents alike.
You’ll build systems that make the data and definitions that matter most to the business easily accessible, like how we calculate net revenue, which shift statuses to commonly exclude, or what a “verified shift” means. All too often things like these live in people’s heads, get rediscovered from scratch in every new analysis, and diverge across teams over time. You’ll develop workflows to enable capturing that meaning as governed, versioned artifacts (dbt semantic models, Snowflake views, structured knowledge files) so every customer can reuse it, regardless of whether that’s a Hex project or a Claude agent.
This increasingly means building for AI as a first-class consumer. AI-assisted analytics is only as good as the data and knowledge context quality underneath it, and you’ll design and build the systems that close the knowledge loop: agentic workflows, peer-reviewed artifact creation, and structured knowledge trees, so that running an analysis also improves the foundation for the next session.
You’ll also keep the foundations solid: the pipelines that extract, load, and transform data from source systems into the warehouse, where availability and freshness are prerequisites for everything else, and the access control framework (Snowflake roles, PII/PHI provisioning, least-privilege at scale) that we own with our Security team for compliance requirements. As we increasingly invest into training and hosting production ML models, you’ll support the engineering teams’ needs to build, deploy, and monitor these systems.
Our customers are our stakeholders, and we prioritize getting to the root cause of their problems and delivering systematic solutions. We measure ourselves by the reliability, adoption, quality, speed of the decisions our data enables.
Our data stack: Snowflake as the warehouse, dbt for transformation, Airbyte and Hevo for ingestion, Hex and Metabase for BI, and various agents (Claude, Codex, Snowflake Cortex, Hex AI, etc.) for AI-assisted analysis. Source systems are largely MongoDB and Postgres.