Key skills
PySparkSQLAIMLData EngineeringDatabricks
About this role
Role Overview
- Build the "Intelligence Layer": Architect the real-time decisioning layer that ingests ML signals and routes them to execution platforms.
- Operationalize Growth ML Models: Partner with Data Science to serve and monitor predictive models.
- Lead the Transition to Harness Engineering: Drive the adoption of AI-native workflows.
- Guarantee Data Trust: Implement automated data sentinels and contract tests.
Requirements
- 2+ years of experience managing engineering teams.
- 3+ years of experience with data engineering technologies including PySpark, Databricks, and SQL.
- Understanding of production data pipelines and data lifecycle management.
- Experience with ML Ops and Model Serving.
Tech Stack
- PySpark
- SQL
Benefits
- Inclusive healthcare and benefits: Comprehensive medical, dental, and vision coverage.
- Lifestyle stipend to support overall well-being.
- Learning and development opportunities to grow personally and professionally.
- Discounted company stock through our ESPP with easy payroll deductions.