Posted:
1/26/2026, 6:46:32 AM
Location(s):
Colorado, United States ⋅ Golden, Colorado, United States
Experience Level(s):
Mid Level ⋅ Senior
Field(s):
Data & Analytics
Workplace Type:
Hybrid
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Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
NLR is seeking a skilled and versatile Data Engineer to join our Data Engineering Group. This role will help to design, build, and maintain scalable and robust data pipelines and architectures that will drive our analytics and data-driven decision-making capabilities. The Data Engineering team is a multi-disciplinary team of data and software engineers, data scientists, and product developers that are at the forefront of developing advanced data solutions for strategic energy analysis at scale. Our work is focused on making energy data and software more accessible, usable, and actionable for researchers and engineers at NLR and beyond.
For this position, we are looking for a candidate with experience working with lifecycle assessment, statistical techniques, model framework development, sensitivity and uncertainty analysis, and energy policy is required. The successful candidate must be able to operate within a large team of analysts and be responsive to quick turnaround requests and handle shifting priorities and project uncertainty.
Key Responsibilities:
Develop bespoke applications using diverse technologies and hybrid (on-prem/cloud/HPC) solutions that meet specific requirements of our varied client projects.
Design, construct, test, and maintain scalable data architectures, data lakes, databases, and datasets, as well as large-scale data processing systems.
Develop high-quality software solutions to manage data workflow, optimization, and retrieval.
Design and implement secure and compliant data models, ETL and analytical pipelines in a distributed and/or hybrid computing environment.
Work closely with data scientists, analysts, and stakeholders to improve data collection, processing methods, and develop tailored software solutions.
Ensure data quality and integrity by adhering to data privacy policies and compliance with data protection regulations.
Proactively research and integrate new technologies, tools, and best practices in data and software engineering.
Train and deploy machine learning models to accelerate data processes for energy research.
Explore the use of large language models to enable better energy systems research.
Develop documentation of data, software, processes and procedures as appropriate.
Our Team
You will join a team where everyone is striving to improve their knowledge of software development best-practices, while caring about creating the best possible solution to cutting edge problems. Our team creates secure, reusable, and efficient code, while supporting a variety of teams:
A dynamic, interdisciplinary research and development environment at a leading national laboratory.
Opportunities to collaborate with a diverse group of experts in software, data, and engineering domains.
Work developing cutting-edge projects and contributing to research in the energy innovation industry.
Access to world-class computational resources and datasets.
A flexible work environment with hybrid remote and onsite work options.
Professional development opportunities, including mentoring, training, and networking.
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* Must meet educational requirements prior to employment start date.
Familiarity with data engineering technologies (e.g., Python, SQL, ETL processes)
Extensive experience developing software and analyzing data with Python.
Ability to translate technical requirements into structured data configurations.
Strong understanding of data management concepts, data quality, and data cleaning.
Experience with a diversity of data technologies.
Strong analytical and problem-solving skills.
Excellent interpersonal skills for engaging with both technical and non-technical users.
Strong written and verbal communication skills for documenting workflows and explaining technical concepts.
Ability to collaborate effectively in a team setting to meet project objectives.
The ideal candidate will have a strong blend of both data engineering and software engineering skills with the ability to work on hybrid tech stacks. Cross-cutting, multi-disciplined candidates will be preferred as we are looking for an engineer who can be a “data-do-all” that can implement high quality, production ready code to solve a variety of research and big data problems.
Strong candidates will have many of the following expertise:
Experience with big data (tens to hundreds of TB)
Experience with version control (git/GitHub)
Basic understanding of data management practices, such as multi-source data collection, workflow management, data storage, security, and availability, data governance & privacy.
Familiarity with agile development
Software and/or data quality assurance (verification and validation, testing, etc.)
Experience with big data tools (e.g., Hadoop, Spark, Kafka, etc.), data pipelines, and software development frameworks
Experience with parallel programming (High Performance Computing experience is a plus) and hybrid computing (on prem and in the cloud)
Familiarity with cloud services (such as AWS S3/Glue/Athena/Lambda, Azure Blob Storage, GCP Storage/BigQuery), data warehousing solutions, and containerization technologies (Docker, Kubernetes).
Experience with SQL, relational databases, and NoSQL databases.
Knowledge of machine learning frameworks, statistical analysis, and algorithm optimization.
Experience working with meteorological data (e.g., wind or solar data in NetCDF of HDF5 format). And cloud-friendly formats, like Parquet.
Excellent analytical, problem-solving, and troubleshooting skills.
Strong communication skills and the ability to collaborate effectively in a multi-project environment with a multidisciplinary team.
Web and API development experience is a bonus.
Prior experience in the energy sector or a research environment is a plus.
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The anticipated closing window for application submission is up to 30 days and may be extended as needed.
NLR takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.
* Based on eligibility rules
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
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All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.
Website: https://www.nrel.gov/
Headquarter Location: Golden, Colorado, United States
Employee Count: 1001-5000
Year Founded: 1977
IPO Status: Private
Last Funding Type: Grant
Industries: Clean Energy ⋅ CleanTech ⋅ Energy ⋅ Renewable Energy