Job Description
📋 Description Own data platform end-to-end: ingestion, transformation, orchestration, ML/streaming Build scalable data onboarding for customers and partners to speed value Run data systems with production discipline: monitoring, SLAs, incidents Create data foundation for AI/ML inputs, training, and feature infra Establish governance: access controls, data classification, audit trails Hire, develop, and lead a high-performing data engineering team 🎯 Requirements 10+ years in data or software, scaling teams of 10+ engineers Hands-on with Snowflake/Databricks, dbt, Airflow; Kafka/Kinesis; AWS preferred Built data systems for production ML: feature stores, real-time inference Operational excellence in data: monitoring, SLAs, incident response, data quality Delivering customer-facing data products (reports, analytics, APIs) in B2B SaaS Architectural judgment: build vs buy, design for change, sequencing investments 🎁 Benefits Generous equity grant, become an owner in our company Comprehensive benefits package Flexible PTO and hybrid work schedules One-time work-from-home allowance Hubs in Los Angeles, San Francisco, Toronto, and Raleigh with hybrid schedules Company events and team-building activities
