Data Engineer

As a Data Engineer, you will:
Infrastructure & Pipelines
Own and maintain our data architecture end-to-end: S3, Databricks compute and administration, pipelines, logging, and our internal tooling
Keep the platform healthy and reliable - the data we serve feeds product decisions and customer-facing AI, so correctness and uptime matter
Integrate new data sources and maintain existing ones, handling the messy realities (format changes, awkward upstream systems like NetSuite, schema drift)
Performance & Cost
Identify bottlenecks and optimize for both compute and cost - parallelize workloads, tune table and cluster settings, and keep our Databricks spend sane as we scale. We use AI coding tools heavily to move fast here, but the engineering judgment is yours
Data Access & Reliability
Build and maintain the semantic layer that exposes our data reliably and consistently to analysts and AI tools, so the same question always returns the same trustworthy answer
Implement PII handling and row- and column-level security so sensitive data stays protected everywhere it's consumed.