Okay, I've searched for Data & Analytics internship positions in Costa Mesa, CA, focusing on strong SQL skills, AWS cloud platform experience, and candidates currently pursuing degrees in Data Science or related fields. I have found 24 relevant internship opportunities for you.

Sure. Here's the analysis:

Job Analysis:

This Data & Analytics Intern role is fundamentally designed to immerse a motivated student in the practical application of data-driven decision-making within a dynamic tech business environment. The core purpose is to support enterprise-level data initiatives by assisting in data querying, management, dashboard development, and cross-functional collaboration, contributing directly to business insights and operational improvements. The role requires not only technical proficiency—specifically advanced SQL skills, familiarity with cloud platforms (notably AWS), and exposure to both relational and NoSQL databases—but also an ability to function effectively within agile frameworks using tools like Jira. The candidate must be detail-oriented, capable of managing multiple priorities, and flexible in tackling ambiguous and evolving tasks, from sprint planning to adhoc data analysis. Success will be measured by the intern’s ability to translate large and complex datasets into meaningful, actionable insights that support product, engineering, and business teams, as well as their capacity to learn, document, and contribute to scalable data systems. This position is a blend of technical execution and collaborative communication, preparing the intern to handle the complexities of real-world data projects and cross-team dependencies in a fast-paced environment.

Company Analysis:

Lensa occupies a significant position as a tech-driven career platform innovating recruitment via advanced machine learning and data analytics. As a market disruptor focused on enhancing the efficiency and personalization of job matching, Lensa’s culture likely emphasizes innovation, agility, and a mission-driven approach—putting people first through smarter technology. The presence of a large, skilled R&D team and multiple US offices indicates a global yet collaborative work environment where data science and software development intersect. For this intern role, the company’s values translate into high expectations for analytical rigor, proactive problem-solving, and adaptability. Because Lensa is deeply invested in transforming job search, the intern will have both the visibility and impact potential to influence strategic data initiatives that power the platform. This role likely sits at a pivotal nexus within cross-functional teams and connects junior technical contributors closely with leadership through mentorship, making it a strong opportunity for career growth within a forward-thinking, technology-centric organization focused on scaling its services and innovation footprint.

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

• Behavioral: Tell me about a time when you had to manage multiple priorities for a data project. How did you ensure deadlines were met without compromising quality?
• Behavioral: Describe an experience where you collaborated with cross-functional teams. How did you handle differing expectations or communication challenges?
• Behavioral: Can you share an example of when you identified a problem with data quality or integrity? How did you approach resolving it?
• Behavioral: How do you stay detail-oriented and motivated when working independently on data analysis tasks?
• Technical: How would you approach designing a query to optimize performance on a large dataset with multiple joins and filters?
• Technical: What experience do you have with AWS data services like Redshift, Lambda, or S3? Can you explain how you have used or would use these in a data pipeline?
• Technical: Describe how you would create a dashboard to highlight key performance indicators for a business unit unfamiliar with data analytics.
• Technical: How familiar are you with agile methodologies and tools such as Jira? How have you used these in managing data projects or internship/work tasks?
• Situational: Imagine you’re tasked with cleaning and transforming a messy dataset from multiple sources to prepare for analysis, with a tight deadline. What steps do you prioritize, and how do you communicate progress?
• Situational: Suppose you notice conflicting data trends between reports generated by different teams. How would you investigate and resolve these discrepancies?
• Situational: If you encounter ambiguity in user requirements for a data visualization during sprint planning, how would you clarify and ensure mutual understanding before proceeding?
• Company Fit: What about Lensa’s mission to transform job search resonates with you personally and professionally?
• Company Fit: How do you see this internship aligning with your career goals in data science or analytics?
• Company Fit: Given Lensa’s emphasis on data-driven decision-making and collaboration, what unique qualities or experiences would you bring to the team?
• Questions for Interviewer: How does the data & analytics team at Hyundai AutoEver America collaborate with other business units throughout the internship program?
• Questions for Interviewer: What are some examples of projects past interns have contributed to that had meaningful business impact?
• Questions for Interviewer: How does Lensa support the professional development and mentorship of interns in data roles?