Position DescriptionThe 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- Cloud Architecture and Backend Infrastructure: Design, implement, and maintain scalable, high-availability AWS cloud architecture and backend systems for real-time and batch data pipelines, storage, and processing supporting measurement and modeling operations.
- Data Pipelines, Processing and Quality Control: Develop, operate, and optimize automated workflows for data ingestion, validation, quality control, transformation, post-processing, reprocessing/backfills, archival, and distribution of high-frequency/large-scale datasets.
- Data Access, APIs and Applications: Design and maintain RESTful APIs, web applications, dashboards, and data access tools to enable secure visualization, analysis, and distribution of processed data and modeling products to researchers, partners, and stakeholders.
- Reliability, Monitoring and Operations: Ensure system reliability, observability, security, and performance through monitoring, alerting, incident response, backups, disaster recovery, and cost-optimized operations.
- Collaboration and Development Lifecycle: Collaborate with researchers and stakeholders to translate scientific/operational requirements into technical solutions; manage the full software development lifecycle including requirements, design, implementation, testing, deployment, documentation, and ongoing support.
Preferred QualificationsExperience with real-time/event-driven architectures and operational modeling or scientific data workflows. Familiarity with time-series databases, data lakes, infrastructure as code, observability tools, and containerization.
Experience with geospatial, atmospheric, environmental, or other scientific/engineering datasets. Knowledge of web application development, dashboards, or basic mobile app integration (iOS/Android). Ph.D. or advanced degree in Computer Science, Engineering, Atmospheric Science, or a related field.
Cloud architecture, AWS services, backend software development, largescale data pipeline design, API development, database management, time-series and scientific data workflows, system monitoring, cybersecurity, CI/CD, version control, containerization, and infrastructure automation. The ideal candidate will also have experience working with geospatial, atmospheric, environmental, or engineering datasets and the ability to translate research and operational needs into reliable, scalable, production-grade technical systems.
Required QualificationsBachelor's degree in computer science, software engineering, information technology or a related field. Three years of related experience.
Safety InformationAdherence to robust safety practices and compliance with all applicable health and safety regulations are responsibilities of all TTU employees.
Pay StatementCompensation 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 AbilitiesSignificant experience in backend or data platform engineering. Strong experience building scalable, production-grade backend services and APIs (Java and/or Python preferred). Proven experience designing, implementing, and operating large-scale data pipelines, including data validation, quality control, reprocessing, backfills, and handling high-frequency/time-series datasets. Solid experience with AWS cloud services (e.g., S3, Lambda, EC2, and related tools) and cloud architecture best practices. Strong knowledge of API design, distributed systems, version control, CI/CD, and modern development workflows. Demonstrated ability to build and maintain reliable, observable, and secure production systems.
