Data Engineer

GridCARE • Redwood City, CA

64d

About The Position

GridCARE solves data center developers' most urgent bottleneck — immediate access to power — through a pioneering physics-based generative AI platform that unlocks gigawatts of near-term capacity from today’s grid. Partnering with utilities, GridCARE applies a proprietary playbook to create additional network capacity on existing transmission infrastructure without costly upgrades or multi-year delays. Founded at Stanford’s Doerr School and backed by leading investors in Energy and AI, GridCARE is working with major technology and data center companies to accelerate interconnection requests for large-load and data center projects. As a fast-growing startup, we are seeking a skilled Data Engineer to help develop data-driven solutions that have real-world impact.

Requirements

• Bachelor’s or higher in Computer Science, Data Science, Electrical Engineering, or a related quantitative field.
• Proficiency with cloud data platforms (e.g., AWS, GCP, Azure) and data warehousing solutions.
• Strong coding skills in Python, SQL, including experience with data manipulation libraries (e.g., Pandas, NumPy) and database interaction and version control (git).
• Ability to write well-documented, tested, and maintainable code.
• Conduct code reviews and contribute to continuous integration and deployment workflows.
• Strong understanding of data modeling, ETL processes, and data governance.
• Knowledge of time-series analysis techniques and non-relational database concepts.
• Excellent problem-solving, communication, and collaboration skills in a fast-paced startup environment.

Nice To Haves

• 2+ years of experience in data engineering, data science, or related areas.
• Experience integrating and tuning 3rd party AI agents.
• Able to leverage AI code development tools such as Cursor, Copilot, and Claude Code to accelerate development.
• Experience working with energy data, including Virtual Power Plants (VPPs), batteries, and control systems.
• Experience with Kubernetes, Terraform, Helm charts and deploying data applications in the cloud.
• Familiar with DevOps pipelines, tools, and requirements.

Responsibilities

• Design and implement data ingestion pipelines into cloud environments, ensuring efficient and scalable data pipelines.
• Identify, find, and integrate new datasets from various sources, both internal and external.
• Analyze time-series and non-relational data, extracting valuable insights.
• Build robust, reusable code to automate data workflows, ensuring reproducibility and scalability.
• Collaborate with software engineers and domain experts to streamline data processes and improve accuracy.
• Evaluate data storage and processing resources, including cloud-native solutions.
• Stay engaged with the latest data engineering and science news, standards, and emerging AI-driven solutions in data management.

Benefits

• Competitive salary and equity.
• Comprehensive benefits package: 401k, healthcare, dental, vision, etc.
• Hybrid work environment with catered lunches and snacks.
• The chance to work at the intersection of AI, automation, and data systems alongside experienced engineers and leading researchers.
• A mission-driven team focused on shaping the future of the energy transition.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Bachelor's degree
• Number of Employees: 11-50 employees