Location: New Orleans,LA, USA
The Data Engineer I oversees the storage, processing, and management of petabytes (PBs) of medical imagery, ensuring the integrity and availability of this critical data. Tulane's School of Science and Engineering is beginning a multi-year project to improve outcomes for prostate and colorectal cancer surgical patients. The project will involve rapidly scanning tumor excisions with high resolution and precision and then using advanced machine-learning techniques to detect residual tumor cells on the surface. The project will create a device to scan and present results to a surgeon while still in the operating room. This state-of-the-art device will be at the forefront of cancer treatment. •Storage Systems: Experience with scalable storage solutions for large datasets (e.g., Hadoop, Apache Spark, AWS S3, Google Cloud Storage). •Database Management: Proficient in managing databases, particularly those storing large volumes of imagery and metadata (e.g., SQL, NoSQL databases). •Data Processing: Strong skills in data processing frameworks and tools (e.g., Apache Kafka, ETL processes). •Backup and Recovery: Expertise in backup and disaster recovery procedures. •Data Integrity: Experience with data validation and ensuring data integrity across large datasets. •Syncing Data: Familiarity with data synchronization techniques and tools. (e.g., Globus) •Proficiency in Python programming. •Problem-Solving: Strong analytical and problem-solving skills with a proactive approach to identifying and addressing data-related issues. •Excellent verbal and written communication skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders. •Bachelor's Degree in Computer Science, Data Engineering, or a related field. •2 years of experience in data engineering or a related role. •Master's Degree in a relevant discipline. •4 years of experience in data engineering or a related role. •Experience in the healthcare industry or working with medical imagery. •Knowledge of cloud platforms and services (e.g., AWS, Azure, Google Cloud). •Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). •Experience with data security and privacy regulations (e.g., HIPAA).