Responsibilities
- Gain comprehensive knowledge of existing data and ML infrastructure, including batch and streaming pipelines, data models, orchestration, and data quality across analytics and production systems.
- Establish strong collaborations with Data Science, Product, and other engineering groups to prioritize key ML and product use cases the platform should support.
- Assume responsibility for a portion of core pipelines and services, enhancing reliability, refining on-call procedures, and setting service level objectives and observability benchmarks.
- Guide the transition of the data platform to a streaming-first, ML-ready design, boosting data freshness, consistency, and discoverability across various domains.
- Develop the initial version of the ML platform layer, incorporating feature pipelines, a feature store, and model serving frameworks to empower Data Science teams with self-service capabilities under shared governance.
- Promote schema governance and data agreements with upstream service teams to minimize fragmentation, standardize core data models, and enhance reliability for analytics and ML users.
- Enhance developer productivity by implementing tools, templates, CI/CD processes, and testing protocols to streamline platform usage for product and ML teams.
- Oversee the end-to-end strategy for the data and ML platform, covering roadmap, architecture, and operational excellence for streaming, batch, and ML workloads.
- Collaborate with Data Science to deploy models into production, managing feature pipelines, serving, monitoring, retraining, and integrating workflows into the data ecosystem.
- Recruit, mentor, and retain a high-achieving data engineering team, defining clear ownership, fostering strong execution practices, and cultivating a culture focused on reliability, scalability, and developer experience.
- Implement operational discipline, including service level objectives, incident management, observability, and change management, aligned with HIPAA/SOC 2 standards in coordination with Security and Compliance.
Benefits
- Comprehensive inclusive healthcare covering medical, dental, and vision, with additional support for gender-affirming care, family and fertility planning, and travel reimbursements for unavailable local healthcare.
- Future savings options through traditional or Roth 401(k) retirement plans featuring a 2% company match.
- Stipends for learning, development, and modern life expenses to support personal and professional growth.
Work Arrangement
Hybrid — San Francisco
Other
- Hybrid roles require office presence 3 days per week for full 8-hour business days.
- San Francisco office permits dogs as part of its workplace program.
