Data Engineer: Lab Data Pipelines & AI Tools

GroundWork Renewables; Albuquerque (NM); On-site; USD 90,000 - 130,000; Full time

Job summary

GroundWork Renewables seeks a Data Engineer to design, build, and maintain internal data infrastructure and pipelines for lab data and instrument measurements.

You will work across database engineering, data tooling, and data governance to ensure high-integrity datasets are ingested, stored, and surfaced for analysis and operations. Collaboration with engineering, laboratory, and operations teams is essential.

Qualifications

• Minimum of 3 years of experience in data engineering, database engineering, ETL/ELT, or related field.
• Experience designing and operating production data pipelines and infrastructure is required.
• Experience in PV measurement or laboratory environments is highly preferred.

Responsibilities

• Design, build, and maintain relational and time-series databases for lab data and operations.
• Develop and manage ETL/ELT pipelines to ingest data from IoT sensors and instruments.
• Build internal tools and dashboards using Streamlit, FastAPI, React to enable data access.
• Apply AI-assisted development tools to accelerate software delivery while maintaining auditability.
• Maintain QA/QC protocols and traceability in line with ISO 17025 or similar standards.

Skills

SQL

ETL/ELT

QA/QC

Data governance

LIMS

CI/CD

Data modeling

Time-series

Communication

Version control

Education

Bachelor's degree in CS/Engineering or related

Tools

PostgreSQL

MySQL

Python

Streamlit

FastAPI

React

Apache Airflow

Dagster

Prefect

SQLAlchemy

Git

Docker

AWS

Azure

GCP

Plotly Dash

Job description

GroundWork Renewables seeks a Data Engineer to design, build, and maintain internal data infrastructure and pipelines for lab data and instrument measurements.

You will work across database engineering, data tooling, and data governance to ensure high-integrity datasets are ingested, stored, and surfaced for analysis and operations. Collaboration with engineering, laboratory, and operations teams is essential.