Data Engineer - Research Systems and Cloud Platform

Texas Tech University • Lubbock, TX

3d

About The Position

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. 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.

Requirements

• Bachelor’s degree in computer science, software engineering, information technology or a related field.
• Three years of related experience.
• Eligibility to drive TTU vehicles, including a valid U.S. driver license and two years of driving experience.
• Must successfully complete a comprehensive background check prior to employment.
• Must 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• Attend meetings related to job functions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior