Scientific Data Engineer for Autonomous Lab Tech

North Carolina State University; Raleigh (NC); On-site; USD 70,000 - 80,000; Full time

Benefits offered by this job

Medical, Dental, and Vision

Flexible Spending Account

Retirement Programs

Disability Plans

Life Insurance

Paid Time Off and Other Leave Programs

12 Holidays Each Year

Tuition and Academic Assistance

Childcare benefits

Wellness Programs

Job summary

NC State University in Raleigh, NC seeks a Data Engineer to build and maintain data infrastructure for the SPEED autonomous-lab initiative. You will integrate instruments, automation, AI, and research data systems to enable reproducible experiments and data-driven discovery in chemistry and materials science.

The role offers a 70k–80k base range and a standard M-F schedule. Collaboration with scientists, IT, and software teams is essential, and you will contribute to scalable data services and

Qualifications

• Bachelor's degree in computer science, data science, engineering, IT, or related field.

Responsibilities

• Build and operate scientific data ingestion, transformation, and processing pipelines.
• Design schemas for samples, experiments, metadata, provenance, and instrument outputs.
• Maintain databases, object/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/recovery, documentation, and user support.

Skills

Python

SQL

ETL pipelines

APIs

Data modeling

Schema design

Git

Linux

Testing

Monitoring

Documentation

Data quality

Provenance

Access control

Backup/recovery

Collaboration

Education

Bachelor's degree in computer science, data science, engineering, IT, or related field

Tools

MongoDB

PostgreSQL

Job description

NC State University in Raleigh, NC seeks a Data Engineer to build and maintain data infrastructure for the SPEED autonomous-lab initiative. You will integrate instruments, automation, AI, and research data systems to enable reproducible experiments and data-driven discovery in chemistry and materials science.

The role offers a 70k–80k base range and a standard M-F schedule. Collaboration with scientists, IT, and software teams is essential, and you will contribute to scalable data services and