Founded in 1964, New York Blood Center (NYBC) has served the tri-state area for more than 60 years, delivering 500,000 lifesaving blood products annually to 150+ hospitals, EMS and healthcare partners. NYBC is part of New York Blood Center Enterprises (NYBCe), which spans 17+ states and delivers one million blood products to 400+ U.S. hospitals annually. NYBCe additionally delivers cellular therapies, specialty pharmacy, and medical services to 200+ research, academic and biopharmaceutical organizations. NYBCe’s Lindsley F. Kimball Research Institute is a leader in hematology and transfusion medicine research, dedicated to the study, prevention, treatment and cure of bloodborne and blood-related diseases. NYBC serves as a vital community lifeline dedicated to helping patients and advancing global public health. To learn more, visit nybc.org. Connect with us on Facebook, X, Instagram, and LinkedIn.

Design, implement, and optimize robust and scalable data pipelines using SQL, Python, and cloud-based ETL tools such as Databricks. Ensure efficient data flow and processing to support large-scale data handling. Develop and refine data models to accurately represent business processes, ensuring they're scalable and fully integrate with our extensive data architecture, including Big Data frameworks like Spark. Enhance our overarching data architecture strategy, assisting in decisions related to data storage, consumption, integration, and management within cloud environments (Azure, AWS, or Google Cloud). Lead and contribute within Agile/SCRUM frameworks to ensure timely and efficient project deliveries. Actively participate in sprints and stand-ups, applying these methodologies to streamline development. Partner with data scientists, BI teams, and other engineering teams to understand and translate complex data requirements into actionable engineering solutions. Guide and mentor junior data engineers, promoting best practices in SQL, Python, and cloud technologies, and fostering a culture of continuous learning and improvement. Uphold and champion data quality standards and governance policies, ensuring reliability and compliance in all data-related tasks. Monitor and enhance the performance of data infrastructure, proactively identifying and resolving bottlenecks or inefficiencies in cloud and Big Data environments. Stay abreast of emerging data engineering and AI technologies and methodologies, recommending and implementing innovative tools or practices as appropriate. Generate comprehensive documentation for data processes, pipelines, and architectures to ensure clarity and ease of maintenance for the team, including detailed descriptions of cloud and Big Data implementations. Telecommuting permitted.

Master's degree in Data Science, Computer Science, Information Technology, or closely related field and 3 years of experience in the position offered or a related role; or a Bachelor’s degree in the above mentioned fields and 5 years of experience in the position offered or a related role. Requires 2 years of experience in all of the following: data engineering; designing, implementing, and optimizing databases and data pipelines; SQL Server, Oracle, or other relational database management systems (RDBMS); SQL and Python for advanced data manipulation and analytics; data modeling and architecture for both analytics and transactional systems within large-scale environments; at least one major cloud data platform (Azure, AWS, Google Cloud) with practical application in data engineering projects; Spark and Cloud ETL tools like Databricks, focusing on scalability and real-time processing capabilities; and developing data models for integration and analysis that support business intelligence and data analytics initiatives.

SALARY: $125,000.00/yr. - $150,000.00/yr.

LOCATION: 310 East 67th Street NY, NY 10065