- Manage, hire, and coach a team of data engineers and applied data scientists.
- Partner with cross-functional leaders to translate business needs into technical requirements.
- Serve as a thought partner on leveraging data, AI, and automation for product and operational improvements.
- Drive the architecture and delivery of scalable batch and streaming pipelines.
- Oversee productionization of ML models and algorithmic systems.
- Champion data reliability, quality, privacy, and governance through self-service tools.
- Improve system performance, debugging speed, and deployment velocity.
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