Senior Data Engineer

Position Summary

The Senior Data Engineer serves as a top-level technical contributor and lead for complex data and analytics initiatives that align technology solutions with clinical, operational, and strategic priorities. This role designs, builds, and operates secure, scalable data pipelines and curated datasets that power analytics, reporting, and advanced AI/ML use cases supporting patient care, administrative decision-making, and improved outcomes. This position partners closely with clinical and operational leaders, analytics teams, vendors and IT stakeholders to translate business needs into reliable data products.

The Senior Data Engineer leads the end-to-end development lifecycle—data ingestion, transformation, modeling, testing, deployment, and monitoring—while championing modern engineering practices (CI/CD, data quality automation, observability, documentation, and governance). Recognized across the organization for expertise in data architecture, engineering standards, and platform modernization.

• Lead design and delivery of enterprise-grade data pipelines (ETL/ELT) using SQL/Python, supporting high-volume, high-complexity healthcare data.
• Build and optimize a modern lakehouse architecture using Azure services and Databricks, including Delta Lake patterns and performance tuning.
• Implement and maintain medallion architecture (bronze/silver/gold): ingestion, standardization, and curated semantic datasets for analytics and downstream consumption.
• Develop scalable transformation and modeling layers using dbt (or equivalent) and data modeling best practices (Kimball, dimensional modeling, star schemas, conformed dimensions).
• Establish and enforce data quality and reliability standards (tests, reconciliation, SLA monitoring, anomaly detection, lineage/metadata).
• Implement CI/CD for data pipelines and dbt projects (Git-based workflows, automated testing, release pipelines via Azure Dev Ops/Git Hub Actions).
• Collaborate with reporting & analytics, data science, data governance and platform systems & architecture teams to enable self-service access to trusted datasets and accelerate insight delivery.
• Provide technical leadership on architecture decisions, security/privacy considerations, performance optimization, and cost management.
• Create and maintain technical documentation, data contracts, and operational runbooks; contribute to engineering standards and patterns.
• Coordinate across medical center and university entities and evaluate external tools/partners to adopt innovative methods and improve delivery.

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or related field (or equivalent practical experience).
• 4+ years of progressive experience in data engineering, data warehousing, or analytics engineering (healthcare required).
• Advanced proficiency with SQL and strong experience with Python for data engineering.
• Hands‑on experience designing and operating ETL/ELT pipelines and building curated analytics datasets.
• Strong understanding of data modeling, warehousing/lakehouse concepts, and modern data management practices.
• Demonstrated ability to lead large, complex initiatives and deliver outcomes in high‑impact environments.

• An array of retirement plan options, each with a generous employer contribution.
• Affordable health insurance options, including dental, vision and prescription coverage that begin on day one.
• Paid vacation and sick leave, including short and long-term disability and paid parental leave.
• Get the most out of the Public Service Loan Forgiveness program.
• And much more!

Final candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process.

The university is an equal opportunity employer, including veterans and disability.