Lead Clinical Data Engineer

The Lead Clinical Data Engineer role at Yale University focuses on advancing the Aligned Data Warehouse (ADW) for biomedical research. This position supports data pipeline and ETL development, expands data integration capabilities, and enables downstream analytics and research data sharing initiatives for Yale School of Medicine and Yale New Haven Health System.

As a senior technical specialist, you will lead the design and development of the ADW and extend its functionality. The work includes integrating new data sources, building and maintaining ETL and data pipelines, and supporting analytics and research data sharing efforts. You will also help manage troubleshooting for ETL failures and ensure healthcare data privacy and security across relevant systems.

• Design, build, test, maintain, and control data pipelines and ETL jobs to integrate data into the ADW and other research databases.
• Contribute to Dev Ops and documentation by developing standards and procedures for database and data pipeline design, operational management, and ongoing maintenance.
• Design, build, test, maintain, and control additional data management processes, including management and loading of flat files in formats such as csv
  , tsv
  , pipe-delimited
  , XML
  , and JSON
  .
• Facilitate design sessions, code walkthroughs, and peer reviews; produce technical documentation, SOPs, and KBAs.
• Performance tune database objects, stored procedures, ETL jobs, and related scripts to optimize end-user queries and pipeline ETL processing.
• Monitor scheduled ETL jobs and related processes to ensure expected operation and pipeline uptime.
• Lead and coordinate troubleshooting and remediation of ETL job failures in a timely manner.
• Provide world-class customer service in interactions with customers, stakeholders, and other teams.
• Maintain patient privacy and the integrity and security of healthcare data in all databases and systems, including compliance with applicable laws, regulations, and institutional policies related to the Institutional Review Board (IRB), patient privacy, and IT cybersecurity
  .
• Independently research and stay current on new and emerging technologies that Scientific Computing & Data could use to improve capabilities, efficiencies, quality, or operating costs.
• Lead projects and data stewardship strategies.
• Work with the DBA team and vendors to optimize data pipelines.
• Assist with the design, build, test, and performance tuning of reports and dashboards in SSRS
  , Microsoft Power BI
  , or similar business intelligence tools.
• Perform related duties as assigned or requested.

• Extensive experience developing, automating, and optimizing data integration workflows with a focus on Microsoft Fabric Data Pipelines supporting large-scale ingestion, transformation, and integration workloads.
• Proven ability to design, develop, and optimize scalable data models, semantic layers, and storage architectures for enterprise reporting, self-service analytics, operational intelligence, and advanced analytics initiatives.
• Experience developing and maintaining Fabric Notebooks using Py Spark ,
  Spark SQL
  , and related technologies for transformation, enrichment, validation, and automation.
• Demonstrated experience designing and implementing Microsoft Fabric Lake houses
  , Warehouses
  , and enterprise data organization strategies supporting governance, performance, security, and scalability requirements.
• Ability to collaborate with business stakeholders, analysts, architects, and technical teams to translate complex business requirements into scalable data engineering solutions.
• A bachelor's degree in a related area and a minimum of four years of experience in the field or a related area.

• Microsoft SQL Server, T-SQL, SSIS, SQL Agent
• Microsoft Fabric, Microsoft Fabric Data Pipelines, Microsoft Fabric Lake houses, Microsoft Fabric Warehouses
• Metadata-driven dynamic SQL
• Linux, Windows
• OMOP Common Data Model, OHDSI's Observational Medical Outcomes Partnership (OMOP) Common Data Model
• SSRS, Microsoft Power BI
• PySpark, Spark SQL, Fabric Notebooks
• Large Language Models, GPU-based software
• csv, tsv, pipe-delimited, XML, JSON
• Epic's data warehouse;
  Epic's Clarity & Caboodle databases
• PCORnet, OnCore, IRES - IRB

• In-depth knowledge of technology areas impacting the role, including healthcare technology experience.
• Experience integrating electronic health record (EHR), clinical, research, financial, or operational healthcare data in…