Data Engineer
Software Engineering, Data Science · Full-time
Posted on Oct 21, 2026
Reports to: Vice President, EngineeringLocation: Albuquerque, NM (On-Site)Classification: Full-Time, Exempt Company Overview GroundWork Renewables is the solar industry’s trusted full-stack performance partner. A Certified B Corporation and ISO-accredited testing provider, we deliver precise MET data and PV module insights—helping developers, EPCs, and asset owners reduce risk, improve forecasting, and maximize value throughout the project lifecycle. Our services have enabled 1,000+ solar measurement campaigns, helping project developers secure billions in financing by reducing uncertainty with trusted resource data. Backed by a recent strategic investment that positions us for accelerated growth, GroundWork is expanding its U.S. operations. Position Summary GroundWork seeks a Lab Data Engineer to build and maintain the Lab’s databases, turn the data in them into insight that informs decisions, and keep the systems built on them monitored and on track across teams. The role combines three disciplines: data engineering (designing, building, and maintaining the databases and pipelines that make laboratory measurement data reliable and accessible), data science (analyzing that data to guide lab, engineering, and operations decisions), and cross-team monitoring and tracking of the Lab’s data systems. The ideal candidate pairs strong database and analytical skills with familiarity with solar energy measurement, accredited laboratory environments, and regulatory data standards.You will work closely with GroundWork’s lab engineering, laboratory, and operations teams to maintain and monitor the Lab’s data systems, keep them aligned with how the Lab works, and assist with developing the front-end tools (scripts, user interfaces, and dashboards) that connect people to the data back-end. That development work makes regular use of AI assistants such as Claude, Copilot, or similar, with outputs reviewed and tested before they are put to use. This role calls for a technically versatile individual who can move between building systems, analyzing data, and supporting the teams who use both. Key Responsibilities Databases & Data Pipelines: Design, implement, and maintain relational and time-series databases for lab instrument data, environmental measurements, and operational records. Build and manage ETL/ELT pipelines that ingest, transform, and store data from measurement hardware, IoT sensors, and remote sensing platforms. Architect and tune schemas for performance, scalability, and ease of access, and recommend database technologies (SQL, NoSQL, time-series) based on data volume, query patterns, and the Lab’s analysis and reporting requirements. Data Analysis & Decision Support: Analyze data from the Lab’s systems to answer engineering, quality, and operational questions, such as test throughput, instrument and equipment performance, measurement trends, and anomalies. Build reports, visualizations, and statistical analyses that turn raw data into clear recommendations for lab leadership and operations. Define and track the metrics that show how the Lab is performing. Cross-Team Monitoring & Tracking: Work with lab engineering and operations to monitor the health, uptime, and performance of the Lab’s data systems and the processes that feed them. Track issues, requests, and changes across teams through to resolution, and keep systems aligned with lab requirements as they evolve. Serve as the primary point of contact for the Lab’s internal data availability and reporting needs. Front-End Tool Development: Assist with developing the scripts, user interfaces, and dashboards that connect lab staff to the data back-end, using frameworks such as Streamlit, FastAPI, React, Plotly Dash, or similar. Use AI assistants such as Claude, Copilot, or similar to speed up development, reviewing all generated code for correctness, security, and maintainability before it ships. Give non-technical lab staff intuitive ways to query, explore, and export data without direct database access. Data Quality Support: Assist the Lab’s quality personnel with LIMS support, data QC, and record-keeping. Help build and maintain automated checks that flag anomalies, missing data, and calibration drift in incoming instrument and sensor data, and support the data integrity and traceability practices the Lab’s quality system requires. Governance & Documentation: Maintain data dictionaries, schema documentation, data lineage records, and tool documentation consistent with the laboratory quality management system. Support the Lab’s quality team with updates to SOPs and data management plans. Stay current with data engineering, data science, AI tooling, and laboratory informatics practices to keep improving the Lab’s data infrastructure. Qualifications & Experience Experience: Minimum of 3 years of experience in data engineering, data science, data analytics, or a related technical discipline, preferably in a laboratory, engineering, or renewable energy context. Experience designing and maintaining production databases and data pipelines is required, along with experience applying data analysis to inform technical or business decisions. Experience in photovoltaic (PV) testing, solar energy measurement, or a physical laboratory environment is highly preferred. Education: Bachelor’s degree in computer science, software engineering, information systems, data science, statistics, engineering, or a related field; advanced degree or relevant certifications preferred. Skills: Proficiency in SQL and experience with relational databases (PostgreSQL, MySQL, or similar); familiarity with time-series or NoSQL databases a plus. Proficiency in Python (pandas, NumPy, SQLAlchemy, or similar) for data engineering, analysis, and scripting. Hands-on experience designing and operating ETL/ELT data pipelines and workflow orchestration tools (e.g., Apache Airflow, Dagster, Prefect, or similar), including scheduling, dependency management, and pipeline monitoring. Strong analytical and statistical skills, including exploratory data analysis, statistical methods, and data visualization (e.g., Matplotlib, Plotly, Power BI, or similar); ability to turn analysis into clear, actionable recommendations. Experience building or contributing to scripts, web applications, or dashboards (e.g., Streamlit, Dash, FastAPI, React, or similar) that sit on top of a data back-end. Working experience with AI assistants such as Claude, Copilot, or similar for coding, debugging, and analysis; comfort reviewing AI-generated outputs for correctness and suitability in a regulated laboratory data environment. Experience with QA/QC checks for instrument or sensor data, such as validation rules, anomaly flagging, and audit logging; familiarity with laboratory quality standards (e.g., ISO/IEC 17025, GLP) or LIMS platforms is a plus. Familiarity with version control (Git), CI/CD practices, and cloud data platforms (AWS, Azure, or GCP); experience with containerization (Docker) is a plus. Interest in laboratory informatics and data management in accredited or regulated settings; exposure to LIMS (Laboratory Information Management Systems) or similar platforms is a plus. Excellent communication skills; ability to translate complex technical concepts for non-technical colleagues, including lab engineers and business analysts. Approach to Work Aligns with our values: Trustworthy, Caring, Knowledgeable, Trailblazing, Nimble and Meticulous. Works collaboratively and directly with remote multi-functional teams and clients. Presents a positive, ‘can-do’ attitude while working in a multi-project work environment. Self-motivated, punctual, organized, and able to perform work with limited supervision. Able to solve practical problems and deal with a variety of concrete variables in situations where only limited standardization exists. Able to communicate verbally and in writing in a clear, concise, and professional manner. GroundWork is a Certified B Corporation and proud equal opportunity employer. We believe a diverse, equitable, and just team makes our work better, and our field a better place to be. We are committed to building a workplace where people feel welcomed, valued, and supported. We hire, promote, and develop people based on their skills, experience, and potential. We do not discriminate based on age, race, ethnicity, religion, color, sex, national origin, marital status, sexual orientation, gender identity, veteran status, disability, pregnancy status, or any other characteristic protected by law. We are a fair chance employer. We’re committed to building a team that reflects the communities we serve, and we’re actively developing the programs to get us there. This work is ongoing. If you need a reasonable accommodation at any point in the application or interview process, just let us know. Please fill out the form below to apply or email a cover letter and resume to careers@grndwork.com.