Okay, I've searched for Data Analyst roles in San Jose, CA with at least 3 years of experience, requiring advanced SQL and Power BI skills, within the construction or engineering industry, and offering full-time positions. I have found 142 positions matching these criteria for you.

Sure. Here's the analysis:

Job Analysis:

The Data Analyst role at Cupertino Electric is fundamentally about transforming complex, multi-source data into actionable insights that directly enhance operational efficiency and strategic decision-making within a highly technical and project-driven environment. This person is expected to serve as a critical bridge between raw data and business leadership, leveraging advanced analytical tools — particularly Power BI, Databricks, and JD Edwards ERP systems — to build interactive, automated dashboards and reports that illuminate project performance, financial status, and resource allocation in real-time. The emphasis on construction management platforms like Procore and ACC indicates the role requires not just generic data analytics skills but a specialized understanding of industry workflows and challenges. Success in this role means enabling the company to make smarter, faster decisions by ensuring data accuracy, integrity, and accessibility, while continuously improving reporting automation through DevOps collaboration. The position demands both technical rigor — from optimized SQL queries to ETL pipeline maintenance — and strong business partnership skills to translate stakeholder needs into precise data solutions. Candidates will need to navigate complex, variable data sources and ambiguity while exercising autonomous judgment on analytic approaches and reporting methodologies. Early success would be marked by the ability to deliver reliable, impactful reports that improve operational transparency and contribute to process improvements, alongside empowering non-technical users through training and clear communication.

Company Analysis:

Cupertino Electric is a well-established leader in the construction and electrical project sector with a strong reputation for integrity, innovation, and safety cultivated over 70 years. The company’s identity lies in delivering complex, high-profile projects reliably, which places a premium on precision, collaboration, and trust—qualities that directly influence the expectations of the Data Analyst role. The work culture appears to be team-oriented and value-driven, focusing on doing the right thing with well-defined processes, while embracing innovation to improve performance. For a candidate, this translates to a workplace where accountability and quality are non-negotiable, but where there is also room to contribute creative data solutions that align with broader organizational goals. The IT team is positioned as a key enabler of success, suggesting that the Data Analyst will have significant visibility and cross-functional interaction, working alongside data engineers, business leaders, and operational staff. This role is strategically aligned with the company's goal to leverage technology and data to make their project execution more efficient, transparent, and sustainable. Since CEI is not a fast-scaling tech startup but a mature organization focused on continual improvement and operational excellence, the candidate should be prepared to balance innovation with stability and practical impact. The position sits within a tech-savvy but construction-centric environment, which requires not only data expertise but also industry-specific knowledge and the ability to build trust across diverse teams to succeed long-term.

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

• Behavioral: Tell me about a time when you had to gather requirements from stakeholders who had very different needs and priorities. How did you manage to deliver a solution that satisfied everyone?
• Behavioral: Describe an instance where you identified data quality issues that impacted reporting outcomes. How did you approach resolving those issues?
• Behavioral: Can you share an experience where you had to explain a complex technical concept to a non-technical audience? What strategies did you use?
• Behavioral: Tell me about a challenging cross-functional project you worked on. How did you ensure collaboration and alignment among teams?
• Technical: How do you design and optimize complex SQL queries in Databricks to handle large-scale datasets efficiently?
• Technical: Walk me through your process for developing an interactive Power BI dashboard from gathering requirements to deployment. How do you ensure it remains performant and user-friendly?
• Technical: Explain your experience working with construction management software like Procore or ACC. How do you approach integrating and analyzing data from these platforms?
• Technical: Describe how you implement data quality checks and monitoring in a multi-source reporting environment.
• Situational: Imagine a core automated report you manage suddenly shows inaccurate data due to upstream system changes. How would you investigate and fix the issue while communicating with stakeholders?
• Situational: If a business leader requests a complex, custom analysis on short notice that requires data you don’t currently have easy access to, how would you handle it?
• Situational: How would you handle conflicting feedback from different stakeholders about the design and content of a key performance dashboard?
• Company Fit: Why are you interested in working at Cupertino Electric, given its industry and long-standing reputation?
• Company Fit: How do your personal work values align with Cupertino Electric’s commitment to integrity, safety, and innovation?
• Company Fit: What attracts you to a role that requires both deep technical analysis and strong business partnership in the construction industry?
• Questions for Interviewer: Can you describe how the Data Analyst role collaborates with other teams like Data Engineering and Project Management on a daily basis?
• Questions for Interviewer: How does Cupertino Electric measure the impact of its data analytics efforts on project performance and organizational success?
• Questions for Interviewer: What are the biggest challenges the IT team currently faces in supporting data-driven decision-making across the company?