Data Engineer

North Carolina State University is seeking a Data Engineer to support the NSF-funded Programmable Cloud Lab Center’s research mission. In this onsite role in Raleigh, the engineer will build and maintain the data infrastructure that powers the SPEED national autonomous-science user facility, enabling reliable and reproducible scientific experiments.

Role Overview

The Data Engineer will focus on scientific data ingestion, transformation, processing, database and storage services, and data-quality and provenance checks. The work supports experiments across chemistry and materials science by ensuring data can be trusted, traced, and accessed effectively for user workflows.

Responsibilities

• Build and operate scientific data ingestion, transformation, and processing pipelines
• Design schemas for samples, experiments, metadata, provenance, and instrument outputs
• Maintain databases, object or time-series storage, indexing, and data-access services
• Implement automated data-quality, validation, unit, completeness, and provenance checks
• Integrate data systems with laboratory automation, software, AI, and user workflows
• Manage access controls, monitoring, backup and recovery, documentation, and user support
• Develop data dictionaries, API specifications, and schema documentation
• Support FAIR data practices and persistent identifiers
• Assist users with data access, export, and troubleshooting
• Evaluate new databases, storage technologies, and interoperability standards
• Participate in technical reviews, platform commissioning, and sponsor demonstrations

Required Qualifications

• Bachelor’s degree in computer science, data science, engineering, IT, or related field
• Proficiency in Python and SQL for data engineering and automation
• Experience with ETL/ELT pipelines, APIs, data modeling, and schema design
• Knowledge of relational and document databases and structured scientific metadata
• Experience with Git, Linux, testing, monitoring, and technical documentation
• Experience implementing data quality, provenance, identifiers, access control, and backup or recovery processes
• Ability to collaborate with scientists and cross-functional teams including automation, software, AI, and IT

Technologies

• Python
• SQL
• ETL/ELT pipelines
• APIs
• Git
• Linux
• MongoDB
• PostgreSQL

Work Location and Compensation

• Location: Raleigh, NC (onsite)
• Salary: USD 70,000 - 80,000 per yearly

Department Context

The role supports the SPEED program, an NSF-funded national autonomous-science user facility. The department operates self-driving platforms for Expedited Experimental co-Design (SPEED), provides remote access to integrated self-driving laboratories, connects robotics, scientific instruments, AI, and data infrastructure, and enables reproducible experiments in chemistry and materials science. Users include academic, government, and industry research teams.

Benefits

• Medical, Dental, and Vision
• Flexible Spending Account
• Retirement Programs
• Disability Plans
• Life Insurance
• Accident Plan
• Paid Time Off and Other Leave Programs
• 12 Holidays Each Year
• Tuition and Academic Assistance
• Childcare benefits
• Wellness & Recreation Membership
• Wellness Programs

Application and Position Details

• Job Open Date: 09/17/2026
• Anticipated Close Date: 9/30/2026; if posting is still active we are accepting and reviewing applications
• Position Number: 00112331
• Position Type: EPS/SAAO
• FTE: 1.0 (1.0 = 40 hours/week)
• Appointment: 12 Month Recurring
• Mandatory Designation - Adverse Weather: Non Mandatory - Adverse Weather
• Mandatory Designation - Emergency Events: Non Mandatory - Emergency Event
• Department ID: 230101 - Interdisciplinary Programs - SVP
• Valid NC Driver’s License Required: No
• Commercial Driver’s License Required: No

Special Instructions to Applicants

• Please include a resume, cover letter, and contact information for at least three professional references.
• This position is not eligible for visa sponsorship. Applicants must be authorized to work in the United States without the need for current or future sponsorship.