Position Description

The data engineer will design, develop, and manage data infrastructure that powers insights. This role is crucial in transforming raw data into actionable intelligence. Collaborate closely with cross-functional teams to build robust data pipelines and infrastructure that enable data-driven decisions.

Major/Essential Functions

Research-to-Production Engineering

• Collaborate with researchers and data scientists to transform prototype algorithms, analytical workflows, proof-of-concept software, and research applications into scalable, maintainable, production-grade systems. Refactor, integrate, optimize, test, deploy, and support research software throughout its lifecycle.

Cloud Architecture & Backend Infrastructure

• 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.

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.

Required Qualifications

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.

About the Department and/or College

The National Wind Institute (NWI) has evolved from its traditional singular focus on wind hazards to three main research pillars of Energy Systems, Atmospheric Measurement & Simulation, and Wind Engineering. Though all three of these pillars focus on distinct issues, they also maintain common ground via cross cutting themes. All research seeks to benefit communities at micro and macro scales.

Safety Information

Adherence to robust safety practices and compliance with all applicable health and safety regulations are responsibilities of all TTU employees.

Pay Statement

Compensation is commensurate upon the qualifications of the individual selected and budgetary guidelines of the hiring department, as well as the institutional pay plan.

Knowledge, Skills, and Abilities

• 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.