Okay, I've searched for part-time Data Engineering Internship roles in the United States that require proficiency in Python and AWS, offer hourly pay between $16 and$21, and are within the clean transportation or environmental sector. I have found 42 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

This Data Engineering Intern role at CALSTART is fundamentally about building foundational data infrastructure to support the organization's mission of advancing clean transportation. The key purpose is to design, develop, and maintain a scalable data lake and automated pipelines that consolidate diverse data sources—ranging from vehicle performance to infrastructure planning—so that the organization can generate actionable insights driving sustainability and zero-emission transportation initiatives. The intern will work within a collaborative team environment, gaining hands-on experience with cloud-based technologies (primarily AWS), ETL process development, and data visualization tools, which are critical for transforming raw data into meaningful reports and dashboards. Beyond technical skills such as Python, SQL, and AWS familiarity, strong communication and teamwork skills are essential due to the cross-functional nature of this role, requiring interaction with data engineers, analysts, and policy experts. Challenges likely include handling heterogeneous datasets, ensuring data quality and consistency, and balancing automation with maintainability in a mission-driven nonprofit setting. Success will be measured by the intern’s ability to contribute clean, reliable data pipelines and insightful visualizations that directly support CALSTART’s clean transportation goals within the internship period, while growing technical proficiency and documenting processes to enable future scalability.

Company Analysis:

CALSTART operates as a nonprofit catalyst at the intersection of clean transportation technology, policy advocacy, and market adoption acceleration. It occupies a unique industry niche as a mission-driven leader committed to climate change mitigation and equitable access to clean transportation. This distinct positioning means the company likely values innovation, impact, and collaboration over traditional corporate metrics, fostering a culture that is purpose-driven, research-informed, and oriented toward long-term environmental and social benefits. The organization appears to maintain a tight-knit yet diverse team, encouraging transparency, meritocracy, and continuous employee growth. For someone in this Data Engineering Intern role, it means working in an environment where technical contributions have clear real-world implications, but also where adaptability and alignment with the mission are vital. The intern will find themselves in a supportive setting with experienced professionals, gaining visibility across teams working on technology, policy, and business fronts. Strategically, this hire enables CALSTART to build the critical data backbone necessary for evidence-based decision making and advocacy efforts, underscoring the role’s importance beyond simple data management toward enabling mission-driven innovation and scaling impact.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to clean and transform a large, messy dataset. What approach did you take to ensure quality and accuracy?
• Behavioral: Describe an instance where you worked collaboratively to design or improve a technical solution. How did you handle differing opinions within the team?
• Behavioral: Can you share a situation where you had to learn a new technology or tool quickly to complete a project? How did you approach the learning process?
• Behavioral: Give an example of a time when you encountered ambiguity in a project requirement. How did you clarify expectations and move forward?
• Technical: How would you architect a data lake on AWS to support multiple data sources with varying structures and ensure scalability?
• Technical: Walk me through your experience building ETL pipelines. What tools and design patterns do you consider most effective for automation and reliability?
• Technical: What strategies do you use to validate and transform data within a pipeline to maintain data integrity before analysis or visualization?
• Technical: How would you approach creating an interactive dashboard that conveys complex transportation data insights to non-technical stakeholders?
• Situational: Imagine you find significant inconsistencies between two datasets critical to the clean transportation project. How would you investigate and resolve this?
• Situational: If a data pipeline you helped build suddenly fails or runs inefficiently, what steps would you take to troubleshoot and optimize it?
• Situational: Suppose you have to prioritize building multiple data pipelines, but you have limited time and resources. How would you decide what to focus on first?
• Company Fit/Motivation: What attracts you to CALSTART’s mission of transportation decarbonization, and how do you see yourself contributing through this role?
• Company Fit/Motivation: How do your personal values and career goals align with working in a mission-driven nonprofit focused on clean technology?
• Company Fit/Motivation: CALSTART emphasizes collaboration across technology, policy, and business teams. How do you envision navigating and contributing in such an interdisciplinary environment?
• Questions for Interviewer: Can you describe the current team structure and how this internship position interacts with other departments such as policy or engineering?
• Questions for Interviewer: What are the biggest data challenges CALSTART is currently facing, and how would this role contribute to overcoming them?
• Questions for Interviewer: How does CALSTART support intern growth and professional development during the 6-month internship?