Senior AI Platform Engineer - Enterprise Data & ML Ops

Stanford Health Care; California (MO); Hybrid; USD 190,109,000 - 252,101,000; Full time

Job summary

Stanford Health Care seeks a Senior Enterprise Data Engineer to design and build complex data pipelines and curated data structures for use by data analysts. You will consult with other data engineers and support data movement to populate enterprise data structures.

This role partners with data scientists on DevOps, SecOps, and FinOps processes, including automated IaC and monitoring to ensure AI/ML solution quality over time.

Qualifications

• Advanced knowledge of relational databases and data modeling.
• Experience deploying cloud data pipelines and analytics solutions.
• Proficiency with PySpark, notebooks, GitHub and DevOps practices.

Responsibilities

• Design and maintain complex data stores and pipelines to support analytics.
• Lead data modeling standards and govern data quality and metadata.
• Collaborate with data scientists to build AI/ML data solutions and IaC processes.
• Optimize performance of data solutions and perform root-cause analysis.
• Provide project leadership across multiple departments and stakeholders.

Skills

Relational databases

Data modeling

Cloud data platforms

PySpark

Notebooks

GitHub

SQL

DevOps concepts

Data governance

Education

BS/BA degree in Information Technology/Information Systems/Business Analytics/related field

Tools

Databricks

Azure

CI/CD tooling

Job description

Stanford Health Care seeks a Senior Enterprise Data Engineer to design and build complex data pipelines and curated data structures for use by data analysts. You will consult with other data engineers and support data movement to populate enterprise data structures.

This role partners with data scientists on DevOps, SecOps, and FinOps processes, including automated IaC and monitoring to ensure AI/ML solution quality over time.