Senior Data Engineer

New York Blood Center Enterprises•New York, NY

16h•Remote

About The Position

This notice is being provided as a result of the filing of an Application for Permanent Alien Employment Certification for the job offered. Any person may provide documentary evidence bearing on the application to the U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue NW, Room N-5311, Washington, D.C. 20210. NOTICE OF FILING EMPLOYER: New York Blood Center POSITION: Senior Data Engineer

Requirements

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.

Responsibilities

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.