Internship

Job Description

Consider before submitting an application:    

This position is expected to start around May 2025 and continue through the Summer term (approximately August 2025) or into Fall 2025 if available and there is an opportunity to do so. We ask for a minimum of 12 weeks, full-time and on-site, for most internships. Our internship program is for students who are actively enrolled in an academic program. Recent graduates seeking employment after graduation and not returning to school should apply for full-time positions, not internships.

International Students: If your work authorization is through CPT, please consult your school on your ability to work 40 hours per week before applying. You must be able to work 40 hours per week on-site. Many students will be limited to part-time during the academic year.  

Location: Palo Alto, CA

Job Responsibilities

• Perform complex data analysis, transforming raw data into meaningful insights using Splunk, Spark, and Python

• Develop, maintain, and improve CI/CD pipelines to support Extract, Transform, and Load (ETL) applications and ensure data integrity

• Support application-level development, monitoring, debugging, and optimization to maintain system performance and reliability

• Build and enhance data pipelines to track insights on energy market incentives, tariffs, and pricing dynamics for data-driven decision-making

• Deploy scalable data pipelines that transform raw data into structured outputs for advanced analytics, machine learning, and AI-driven insights

• Develop tools and frameworks that enable engineers to efficiently query, summarize, and explore large datasets

• Research, prototype, and integrate a Large Language Model (LLM) to automate data retrieval and power a chatbot that assists engineers in analyzing and interpreting data

• Collaborate with cross-functional teams to design, implement, and optimize data processing workflows for improved efficiency and accuracy

Job Requirements

• Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, or equivalent
• Significant, demonstrated technical contributions towards past projects  
• Programming experience with Python (preferred), MATLAB, and/or JavaScript  
• Experience with continuous integration / continuous deployment  
• Some familiarity with dev-ops tools: Git, Jenkins, Docker, Kubernetes, Splunk, Redis  
• Experience with distributed computing (Spark/Hive/Hadoop)  
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, or Plotly) to present insights effectively