Spare Parts Optimization Strategy Intern

About the role#

SB Energy is seeking a Spare Parts Optimization Strategy Intern to lead the migration and modernization of operational time-series data. This role focuses on transitioning data from the Canary Historian system to Azure Blob Storage to create a scalable, cost-efficient data platform. You will also contribute to the design of systems that allow internal AI tools to query and retrieve this data through natural language. This is a hands-on position requiring the ability to translate open-ended technical challenges into structured, scalable solutions.

What you'll do#

• Analyze and interpret time-series data stored in the Canary Historian system.
• Design and implement components of a scalable data migration pipeline to Azure Blob Storage.
• Transform and structure large datasets to improve storage, query performance, and cost efficiency.
• Define data schemas, partitioning strategies, and storage formats such as Parquet.
• Validate data integrity throughout the migration process.
• Build mechanisms for AI chatbot access, including APIs, query layers, or retrieval pipelines.
• Collaborate with IT and Data Science teams to integrate data into downstream systems.
• Evaluate architectural trade-offs regarding performance, cost, and scalability.
• Document technical designs and present solutions and business impact to stakeholders.

What you'll need#

• Current enrollment in a Bachelor’s degree program in Computer Science, Data Science, Engineering, Mathematics, or a related field.
• Strong programming skills in Python or a similar language.
• Experience working with data using tools such as Pandas or SQL.
• A solid understanding of data structures, algorithms, and system design fundamentals.
• Ability to work effectively both independently and within a team environment.
• Preferred: Experience with cloud platforms (Azure, AWS, or GCP), familiarity with ETL/ELT concepts, and experience with large datasets or time-series data.

Location & details#

• Location: San Francisco, California.
• Work Modality: Hybrid.
• Employment Type: Full-time, paid internship.