Data Engineer - Research Systems and Cloud Platform

Design, implement, and maintain scalable, highly available AWS cloud architecture, backend services, and cloud-native applications supporting real-time and batch measurement, modeling, and scientific data systems. Design software architectures that balance scalability, reliability, maintainability, operational simplicity, and cloud cost. Data Platform & Processing Develop, operate, and optimize automated workflows for high-frequency data ingestion, validation, quality control, transformation, post-processing, historical reprocessing/backfills, archival, and distribution. Design systems that support evolving scientific workflows while maintaining reliable production operations. System Integration & Applications Integrate research software, backend services, databases, APIs, web applications, dashboards, and cloud services into cohesive production systems. Design and maintain secure APIs and backend services supporting researchers, operational users, external partners, and public-facing applications. Support refinement and production deployment of user-facing applications developed during research projects, including web interfaces and dashboards when needed. Reliability & Operations Ensure production systems remain reliable, observable, secure, and maintainable through monitoring, logging, alerting, incident response, backups, disaster recovery, and continuous operational improvement. Deploy, operate, and optimize applications and services using AWS best practices. Collaboration & Software Lifecycle Work closely with researchers, scientists, engineers, and operational stakeholders to translate scientific requirements into robust software solutions. Lead software through the complete lifecycle including architecture, implementation, testing, deployment, documentation, maintenance, and continuous improvement. Driving to attend meetings related to job functions is required.

Significant experience designing and building scalable backend software and distributed systems. Strong experience building production-grade backend services, APIs, and cloud-native applications. Experience transforming prototype, research, or legacy software into maintainable, production-quality systems. Strong experience designing, implementing, and operating large-scale data pipelines, including validation, quality control, reprocessing, backfills, and high-frequency or time-series datasets. Experience integrating multiple software components, databases, cloud services, and applications into reliable end-to-end production workflows. Solid experience designing AWS cloud architectures and deploying production applications using appropriate cloud services. Strong understanding of distributed systems, software architecture, API design, CI/CD, testing, observability, version control, and modern software engineering practices. Demonstrated ability to build reliable, secure, maintainable, and observable production systems., Bachelor’s degree in computer science, software engineering, information technology or a related field. Three years of related experience.

This position requires eligibility to drive TTU vehicles, including a valid U.S. driver license and two years of driving experience.

This position is designated as involving access to critical infrastructure systems and/or research, as defined by Texas Executive Order GA-48. As such, candidates must successfully complete a comprehensive background check prior to employment. Employees are required to comply with all applicable state and federal regulations related to the protection of critical infrastructure. Ongoing employment is dependent upon maintaining eligibility for access and successfully passing periodic security and compliance reviews.

Preferred Qualifications

Experience working closely with researchers or data scientists in a research-to-production environment. Experience with real-time or event-driven architectures. Experience with scientific computing, modeling systems, engineering applications, or environmental data systems. Familiarity with time-series databases, data lakes, infrastructure as code, containerization, and cloud observability tools. Experience developing or supporting web applications, dashboards, or scientific visualization tools. Experience with geospatial, atmospheric, environmental, or engineering datasets. Advanced degree in Computer Science, Engineering, Atmospheric Science, or a related field.