The Principal, Data Engineer builds data infrastructure, leads technical initiatives, and mentors junior team members while driving data-driven solutions across the organization. As a Principal, Data Engineer, a typical day might include the following: Design complex data engineering solutions and define standards Mentor junior engineers and drive infrastructure innovation Build scalable, secure data pipelines with robust monitoring Optimize ETL/ELT workflows for large-scale data processing Architect end-to-end data pipeline solutions from ingestion to consumption Implement real-time and batch processing systems to handle diverse biotech data streams Design fault-tolerant pipelines with appropriate error handling and recovery mechanisms Establish CI/CD practices for data pipeline deployment and testing Develop data transformation logic to support analytical and operational needs Integrate disparate data sources including laboratory instruments, clinical systems, and external APIs Implement data validation frameworks to ensure data integrity throughout the pipeline Manage and organize large datasets Ensure data quality and accessibility for data analysts Implement data lake and data warehouse architectures Monitor data pipeline performance and troubleshoot issues Maintain efficiency and reliability of data systems Implement observability solutions for pipeline monitoring Develop automated alerting systems for pipeline failures or anomalies as needed Build and leverage GenAI solutions to improve performance, speed and efficiency of data engineering team Document data processes and systems as required Ensure compliance with data governance policies.