
location_on9, East 45th Street, Midtown, Manhattan Community Board 5, Manhattan, New York County, New York, 10017, United States
IBM Quantum is building the world's leading quantum computing systems, software, and cloud services. Our mission is to advance the field of quantum computing by creating robust hardware and the software ecosystems that power it.
The Data Engineer in this role is a seasoned specialist focused on Data Integration. You will design and build solutions to transfer data from operational and external environments into the business intelligence landscape. Your expertise ensures the seamless flow of data throughout the entire lifecycle of our business intelligence solutions.
You will work closely with quantum hardware, firmware, cloud, and product teams to turn diverse technical datasets into trusted analytics assets. These assets guide decision-making across IBM Quantum's roadmap, providing insight into quantum hardware performance, system reliability, user workloads, and platform operations.
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
Work model: On-site
9, East 45th Street, Midtown, Manhattan Community Board 5, Manhattan, New York County, New York, 10017, United States
New York, New York
Experience with Lakehouse solutions and architectures, including IBM watsonx.data. Experience with distributed analytics engines such as Presto/Trino, or Apache Spark. Familiarity with data modeling techniques for analytical and reliability engineering use cases. Exposure to data governance concepts such as access control, dataset ownership, lineage, and lifecycle management. Experience operating data pipelines in cloud-based or distributed environments (e.g., hybrid cloud, containerized systems). Experience working with hardware telemetry, infrastructure monitoring data, or high-volume operational datasets. Interest in or exposure to quantum computing, advanced hardware systems, cryogenics, or other deep-technology platforms.
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