Data Engineer

Overview

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The Organization The Pop Health Learning Center ("PHLC") is a California Social Purpose Corporation (SPC) committed to transforming how health care is delivered and experienced across California’s safety net. Established to prioritize social impact over profit, the organization is grounded in a mission to advance health equity and support community‑centered approaches to care for those historically underserved.

PHLC is focused on strengthening the infrastructure required to advance equity‑focused transformation in primary care and population health. This includes designing and managing large‑scale practice transformation initiatives, delivering technical assistance through virtual learning environments and peer‑based engagement, and supporting alignment across systems, funders, and care delivery partners. We serve as a strategic partner to organizations and institutions committed to advancing health equity, with all efforts grounded in a shared goal: building a more just, coordinated, and person‑centered healthcare system that better serves communities historically marginalized by existing models of care.

The Data Engineer, reporting to the Director of Analytics and Impact, will be responsible for designing, building, and maintaining the data infrastructure that powers the Learning Center’s analytics, reporting, and program evaluation. This role ensures that high‑quality, timely data flows seamlessly across systems to enable performance measurement, surface actionable insights, and demonstrate program outcomes.

• Design, develop, and maintain robust and scalable data warehouse solutions on the Amazon Web Services (AWS) platform.
• Build, optimize, and manage ETL/ELT pipelines using AWS tools to ingest data.
• Maintain and deploy ETL jobs that handle data integration and transformation, including native solutions such as Glue or PySpark.
• Design and implement schemas, tables, views, queries, and stored procedures optimized for performance, ensuring data integrity, governance, and security.
• Design and implement data models (star, snowflake) optimized for analytics and reporting.
• Ensure data quality and compliance by implementing validation, auditing, and access‑control frameworks across all stages of data processing.
• Monitor, troubleshoot, and tune ETL jobs and query performance using best practices.
• Develop and manage CI/CD pipelines using AWS Code Pipeline, Code Build, and Git Hub/Git Lab for continuous integration and automated deployments.
• Document data warehouse architecture, ETL/ELT workflows, and data models to maintain transparency and operational continuity.
• Implement and monitor logging, alerting, and incident response mechanisms using Cloud Watch, Cloud Trail, and SNS.
• Stay current with emerging AWS data services and analytics trends to continuously improve data architecture and engineering practices.
• Follow and contribute to established database and data governance standards.
• Ensure compliance with HIPAA and industry security frameworks.

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 5+ years of hands‑on experience in data modeling and data warehouse design.
• 3+ years of experience with AWS Cloud, including deployment, administration, and migration.
• Strong experience with AWS and ETL/ELT and data warehousing.
• Advanced proficiency in SQL and Python for data transformation, stored procedures, and performance optimization.
• Expertise in dimensional modeling and schema design (star/snowflake).
• Deep understanding of AWS data ecosystem — S3, Glue, Lambda, Redshift, Athena, RDS, and Step Functions.
• Strong analytical and problem‑solving skills with the ability to troubleshoot complex data workflows.

• AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Professional.
• Experience with Apache Spark or PySpark on AWS Glue or EMR.
• Experience with BI tools.
• Familiarity with data security best practices in cloud environments (IAM roles, KMS encryption, VPC endpoints).

• Foster a…