Senior Data Engineer: Cloud Data Platforms & ML Enablement

UCLA Health; Los Angeles (CA); On-site; USD 109,000 - 242,000; Full time

Job summary

UCLA Health in Los Angeles, CA seeks a Senior Data Engineer to design and build scalable data pipelines, curate data products, and support analytics, ML, and AI initiatives across clinical, operational, and research domains.

You will advance cloud data capabilities (Azure, Databricks, lakehouse) and champion modern engineering practices, CI/CD, testing, and observability while mentoring engineers and partnering with stakeholders to define robust data solutions and long-term architecture.

Qualifications

• 5+ years of experience in data engineering or related roles.
• Strong Python programming with production-quality code.
• Solid understanding of data warehousing, ETL/ELT, and dimensional modeling.
• Experience designing data pipelines from multiple sources.
• Experience with modern data platforms: Databricks, Spark, Delta Lake, Snowflake, Fabric.
• Working knowledge of cloud platforms: Azure, AWS, or GCP; Azure preferred.
• Experience with orchestration/tools like Azure Data Factory, Databricks Workflows, Airflow.
• Production engineering practices: Git, CI/CD, automated testing, logging, monitoring, release management.
• Experience with ML data workflows, feature engineering, and ML-ready datasets.
• Ability to collaborate with architects, analysts, data scientists, and product teams.
• Strong written and verbal communication; documentation of solutions.

Responsibilities

• Design and build scalable data pipelines and platforms ingesting diverse data sources.
• Develop trusted data products and reusable data models for reporting and analytics.
• Engineer solutions across clinical, operational, financial, and research data domains.
• Advance cloud-based data capabilities using Azure, Databricks, lakehouse architectures.
• Apply modern engineering practices: automated testing, CI/CD, monitoring, and observability.
• Mentor engineers through code reviews and technical sessions.
• Partner with leadership and cross-functional teams to shape long-term data architecture.

Skills

Python

Technical leadership

Code reviews

Communication

Education

Bachelor’s degree in CS/CE/DS

Master’s degree (nice to have)

Tools

Databricks

Spark

Delta Lake

Snowflake

Fabric

Azure

AWS

GCP

Azure Data Factory

Databricks Workflows

Airflow

Job description

UCLA Health in Los Angeles, CA seeks a Senior Data Engineer to design and build scalable data pipelines, curate data products, and support analytics, ML, and AI initiatives across clinical, operational, and research domains.

You will advance cloud data capabilities (Azure, Databricks, lakehouse) and champion modern engineering practices, CI/CD, testing, and observability while mentoring engineers and partnering with stakeholders to define robust data solutions and long-term architecture.