{"schemaVersion":"jobsearcher.job.v1","id":"7d8ec78cd365d578f2eef1e9","url":"https://jobsearcher.com/jobs/7d8ec78cd365d578f2eef1e9","canonicalUrl":"https://jobsearcher.com/jobs/7d8ec78cd365d578f2eef1e9","title":"Data Engineer - IBM Quantum","description":"Introduction\r\nIBM Quantum is building the world's leading quantum computing systems, software, and cloud services. The Data Engineer in this role will design and operate the data pipelines that power insight into quantum hardware performance, system reliability, user workloads, and platform operations. You will work closely with quantum hardware, firmware, cloud, and product teams to turn diverse technical datasets into trusted analytics assets that guide decision-making across IBM Quantum's roadmap.\r\nYour role and responsibilities\r\nAs a seasoned Data Engineer specializing in Data Integration, you will design and build solutions to transfer data from operational and external environments to the business intelligence environment. Your expertise will ensure the seamless flow of data throughout the business intelligence solution's lifecycle. Your primary responsibilities will include:\r\nDesign Data Integration Solutions: Create and implement Extract, Transform, and Load (ETL) processes to facilitate data transfer between environments\r\nDevelop ETL Processes: Build and maintain efficient ETL processes to ensure accurate and timely data flow, adhering to best practices and industry standards.\r\nEnsure Seamless Data Flow: Monitor and troubleshoot data integration issues, collaborating with stakeholders to resolve problems and optimize data flow.\r\nOptimize Data Integration Solutions: Continuously evaluate and improve data integration solutions, identifying opportunities for process improvements and efficiency gains.\r\nRequired technical and professional expertise\r\nDesign, build, and maintain scalable, reliable data pipelines supporting analytics, operational dashboards, and hardware performance insights for IBM Quantum systems.\r\nContribute towards building IBM Quantum's Lakehouse by implementing scalable data connectors.\r\nDevelop and operate ETL/ELT workflows and tooling with a focus on data quality, accuracy, timeliness, and continuous improvement.\r\nApply advanced SQL skills using PostgreSQL and Presto to support analytical workloads, including complex queries and performance tuning.\r\nBuild and operate orchestration workflows in Apache Airflow, including dependency management, retries, backfills, monitoring, and operational reliability.\r\nImplement data transformations and validations using Python (e.g., pandas and related libraries).\r\nSupport large-scale batch processing for high-volume, heterogeneous datasets, including system telemetry, experiment metadata, cloud operations data, and device performance metrics.\r\nWork with streaming platforms such as Apache Kafka or IBM Event Streams to consume event-driven data from distributed quantum systems and services.\r\nApply streaming architecture concepts including topics, partitions, consumer groups, and schema evolution.\r\nIntegrate multiple technical data sources—quantum hardware telemetry, calibration data, experiment logs, job execution data, user activity, system health metrics—into trusted analytical datasets.\r\nCollaborate with quantum hardware, software, product, SRE, and analytics teams to translate requirements into robust, production-ready data solutions.\r\nUse Git-based version control, contribute via code reviews, and follow industry-standard software engineering best practices.\r\nPreferred technical and professional experience\r\nExperience with Lakehouse solutions and architectures, including IBM watsonx.data\r\nExperience with distributed analytics engines such as Presto/Trino, or Apache Spark\r\nFamiliarity with data modeling techniques for analytical and reliability engineering use cases.\r\nExposure to data governance concepts such as access control, dataset ownership, lineage, and lifecycle management.\r\nExperience operating data pipelines in cloud-based or distributed environments (e.g., hybrid cloud, containerized systems).\r\nExperience working with hardware telemetry, infrastructure monitoring data, or high-volume operational datasets.\r\nInterest in or exposure to quantum computing, advanced hardware systems, cryogenics, or other deep-technology platforms.\r\nIBM 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.\r\nJ-18808-Ljbffr","company":"IBM Computing","rawCompany":"ibm computing","city":"Chicago","state":"IL","isRemote":false,"isActive":false,"createdAt":"2026-07-04T02:42:42.816Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer - IBM Quantum","description":"Introduction\r\nIBM Quantum is building the world's leading quantum computing systems, software, and cloud services. The Data Engineer in this role will design and operate the data pipelines that power insight into quantum hardware performance, system reliability, user workloads, and platform operations. You will work closely with quantum hardware, firmware, cloud, and product teams to turn diverse technical datasets into trusted analytics assets that guide decision-making across IBM Quantum's roadmap.\r\nYour role and responsibilities\r\nAs a seasoned Data Engineer specializing in Data Integration, you will design and build solutions to transfer data from operational and external environments to the business intelligence environment. Your expertise will ensure the seamless flow of data throughout the business intelligence solution's lifecycle. Your primary responsibilities will include:\r\nDesign Data Integration Solutions: Create and implement Extract, Transform, and Load (ETL) processes to facilitate data transfer between environments\r\nDevelop ETL Processes: Build and maintain efficient ETL processes to ensure accurate and timely data flow, adhering to best practices and industry standards.\r\nEnsure Seamless Data Flow: Monitor and troubleshoot data integration issues, collaborating with stakeholders to resolve problems and optimize data flow.\r\nOptimize Data Integration Solutions: Continuously evaluate and improve data integration solutions, identifying opportunities for process improvements and efficiency gains.\r\nRequired technical and professional expertise\r\nDesign, build, and maintain scalable, reliable data pipelines supporting analytics, operational dashboards, and hardware performance insights for IBM Quantum systems.\r\nContribute towards building IBM Quantum's Lakehouse by implementing scalable data connectors.\r\nDevelop and operate ETL/ELT workflows and tooling with a focus on data quality, accuracy, timeliness, and continuous improvement.\r\nApply advanced SQL skills using PostgreSQL and Presto to support analytical workloads, including complex queries and performance tuning.\r\nBuild and operate orchestration workflows in Apache Airflow, including dependency management, retries, backfills, monitoring, and operational reliability.\r\nImplement data transformations and validations using Python (e.g., pandas and related libraries).\r\nSupport large-scale batch processing for high-volume, heterogeneous datasets, including system telemetry, experiment metadata, cloud operations data, and device performance metrics.\r\nWork with streaming platforms such as Apache Kafka or IBM Event Streams to consume event-driven data from distributed quantum systems and services.\r\nApply streaming architecture concepts including topics, partitions, consumer groups, and schema evolution.\r\nIntegrate multiple technical data sources—quantum hardware telemetry, calibration data, experiment logs, job execution data, user activity, system health metrics—into trusted analytical datasets.\r\nCollaborate with quantum hardware, software, product, SRE, and analytics teams to translate requirements into robust, production-ready data solutions.\r\nUse Git-based version control, contribute via code reviews, and follow industry-standard software engineering best practices.\r\nPreferred technical and professional experience\r\nExperience with Lakehouse solutions and architectures, including IBM watsonx.data\r\nExperience with distributed analytics engines such as Presto/Trino, or Apache Spark\r\nFamiliarity with data modeling techniques for analytical and reliability engineering use cases.\r\nExposure to data governance concepts such as access control, dataset ownership, lineage, and lifecycle management.\r\nExperience operating data pipelines in cloud-based or distributed environments (e.g., hybrid cloud, containerized systems).\r\nExperience working with hardware telemetry, infrastructure monitoring data, or high-volume operational datasets.\r\nInterest in or exposure to quantum computing, advanced hardware systems, cryogenics, or other deep-technology platforms.\r\nIBM 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.\r\nJ-18808-Ljbffr","datePosted":"2026-07-04T02:42:42.816Z","dateModified":"2026-07-04T02:42:42.816Z","hiringOrganization":{"@type":"Organization","name":"IBM Computing","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Chicago","addressRegion":"IL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"7d8ec78cd365d578f2eef1e9"},"url":"https://jobsearcher.com/jobs/7d8ec78cd365d578f2eef1e9"}}