Hiring: Data Engineer Company: IBM Location: Austin, TX Job Posted Time: 2026-09-10 07:40:09 Employment Type: Hybrid Target Skills & Keywords : Airflow, Data Pipeline, ELT, ETL, Event-Driven, Firmware, Git, Kafka, Pandas, Python, Spark About the job Experience: •Operational 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. •Interest in or exposure to quantum computing, advanced hardware systems, cryogenics, or other deep-technology platforms. Required Skills: •As a 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: •Design Data Integration Solutions: Create and implement Extract, Transform, and Load (ETL) processes to facilitate data transfer between environments •Develop ETL Processes: Build and maintain efficient ETL processes to ensure accurate and timely data flow, adhering to best practices and industry standards. •Ensure Seamless Data Flow: Monitor and troubleshoot data integration issues, collaborating with stakeholders to resolve problems and optimize data flow. •Optimize Data Integration Solutions: Continuously evaluate and improve data integration solutions, identifying opportunities for process improvements and efficiency gains. Qualifications: •Master's Degree •Required Technical And Professional Expertise •Design, build, and maintain scalable, reliable data pipelines supporting analytics, operational dashboards, and hardware performance insights for IBM Quantum systems. •Contribute towards building IBM Quantum’s Lakehouse by implementing scalable data connectors. •Develop and operate ETL/ELT workflows and tooling with a focus on data quality, accuracy, timeliness, and continuous improvement. •Build and operate orchestration workflows in Apache Airflow, including dependency management, retries, backfills, monitoring, and operational reliability. •Implement data transformations and validations using Python (e.g., pandas and related libraries). •Support large-scale batch processing for high-volume, heterogeneous datasets, including system telemetry, experiment metadata, cloud operations data, and device performance metrics. •Interface directly with streaming platforms such as Apache Kafka or IBM Event Streams to consume event-driven data from distributed quantum systems and services. •Integrate multiple technical data sources—quantum hardware telemetry, calibration data, experiment logs, job execution data, user activity, system health metrics—into trusted analytical datasets. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!