Southern California Edison (Sce) Business Intelligence Interview Guide

Getting ready for a Business Intelligence interview at Southern California Edison (SCE)? The SCE Business Intelligence interview process typically spans 4–6 question topics and evaluates skills in areas like data analysis, dashboard design, ETL pipelines, and stakeholder communication. Interview preparation is especially important for this role at SCE, as candidates are expected to leverage data-driven insights to support utility operations, optimize business processes, and present findings to both technical and non-technical audiences in a regulated, customer-focused environment.

In preparing for the interview, you should:

• Understand the core skills necessary for Business Intelligence positions at Southern California Edison.
• Gain insights into SCE’s Business Intelligence interview structure and process.
• Practice real SCE Business Intelligence interview questions to sharpen your performance.

At Interview Query, we regularly analyze interview experience data shared by candidates. This guide uses that data to provide an overview of the Southern California Edison Business Intelligence interview process, along with sample questions and preparation tips tailored to help you succeed.

Southern California Edison (SCE), a subsidiary of Edison International, is one of the nation’s largest investor-owned utilities, serving nearly 14 million people across a 50,000 square-mile territory in central, coastal, and southern California. With a customer base of about 4.9 million residential and business accounts, SCE is responsible for maintaining extensive energy infrastructure, including over 115,000 miles of transmission lines and 1.5 million electricity poles. Regulated by the California Public Utilities Commission and the Federal Energy Regulatory Commission, SCE is committed to investing in and modernizing its electric system to support California’s dynamic population and economy. In a Business Intelligence role, you will contribute to data-driven decision-making that supports SCE’s mission of delivering reliable, sustainable energy.

As a Business Intelligence professional at Southern California Edison (SCE), you are responsible for transforming data into actionable insights that support strategic decision-making across the organization. You will gather, analyze, and visualize data from various sources to identify trends, optimize operations, and drive efficiency in energy delivery and business processes. Working closely with cross-functional teams, you will develop dashboards, generate reports, and present findings to stakeholders to inform planning and improve performance. Your work directly contributes to SCE’s mission of providing reliable, sustainable energy solutions by enabling data-driven strategies and continuous improvement.

2.1 Stage 1: Application & Resume Review

The process begins with a thorough review of your application and resume by the SCE talent acquisition team. At this stage, emphasis is placed on your experience with data analytics, business intelligence tools, data visualization, ETL processes, and your ability to translate data into actionable business insights. Demonstrated experience with designing dashboards, data warehousing, and communicating complex findings to non-technical stakeholders is highly valued. To prepare, ensure your resume highlights relevant technical skills (such as SQL, Python, Power BI, Tableau), successful BI projects, and your impact on data-driven decision-making.

2.2 Stage 2: Recruiter Screen

If your background aligns with the role, a recruiter will reach out for a phone screen. This conversation typically lasts 30–45 minutes and focuses on your motivation for applying to SCE, your understanding of the utility/energy sector, and a high-level overview of your technical and communication skills. Expect questions about your career trajectory, strengths and weaknesses, and your interest in business intelligence at SCE. Prepare by researching SCE’s mission, recent business intelligence initiatives, and formulating clear reasons for your interest in the company and role.

2.3 Stage 3: Technical/Case/Skills Round

The next stage involves one or more technical assessments conducted virtually or in-person by BI team members, data engineers, or analytics managers. You may face a mix of case studies, technical problem-solving exercises, and data challenges. Common topics include designing data pipelines, ETL solutions, data cleaning, A/B testing, and developing dashboards for business users. You might be asked to interpret business scenarios (such as evaluating the impact of a pricing promotion), analyze messy datasets, or design a data warehouse for a new service. Preparation should focus on hands-on practice with SQL, Python, data modeling, and the ability to clearly explain your analytical approach and recommendations.

2.4 Stage 4: Behavioral Interview

This round, often conducted by a hiring manager or a BI team lead, assesses your interpersonal and communication skills, adaptability, and alignment with SCE’s values. You will be asked to describe past projects, challenges you’ve faced in data initiatives, how you’ve made data accessible to non-technical users, and your experience presenting complex insights to varied audiences. Prepare specific stories that demonstrate your problem-solving skills, stakeholder management, and your ability to drive business outcomes through data.

2.5 Stage 5: Final/Onsite Round

The final stage typically consists of several back-to-back interviews with cross-functional stakeholders, senior BI leaders, and potential team members. This round may include a technical presentation, in-depth case discussions, and scenario-based questions involving business intelligence strategy, data governance, and cross-departmental collaboration. You may be asked to walk through a recent project, justify your technical choices, or respond to real-world business challenges relevant to SCE’s operations. Preparation should include reviewing your portfolio, practicing clear and concise presentations, and demonstrating your ability to bridge technical and business perspectives.

2.6 Stage 6: Offer & Negotiation

Candidates who successfully navigate the process will receive an offer from SCE’s HR team. This stage involves discussions about compensation, benefits, and start date, as well as clarifying any final questions about the role or team. Be prepared to negotiate based on your experience, market benchmarks, and the unique value you bring to the BI team.

2.7 Average Timeline

The typical Southern California Edison Business Intelligence interview process spans 3–5 weeks from initial application to final offer. Highly qualified candidates may progress more rapidly, completing the process in as little as 2–3 weeks, while standard timelines allow for a week between each round to accommodate scheduling and feedback. Technical assessments and onsite interviews are generally scheduled within a week of each other, and prompt communication from the recruiting team ensures a transparent and efficient process.

Next, let’s explore the specific interview questions you may encounter throughout the SCE Business Intelligence interview process.

3.1 Data Analysis & Experimentation

Business Intelligence at Southern California Edison requires strong analytical skills to design experiments, measure impact, and translate findings into actionable business decisions. You’ll be evaluated on your ability to structure analyses, interpret results, and recommend data-driven strategies that align with organizational goals.

3.1.1 You work as a data scientist for ride-sharing company. An executive asks how you would evaluate whether a 50% rider discount promotion is a good or bad idea? How would you implement it? What metrics would you track?
Frame your answer by proposing an experimental design (such as A/B testing), outlining key metrics (e.g., conversion, retention, revenue impact), and discussing how you would interpret both short- and long-term effects.

3.1.2 The role of A/B testing in measuring the success rate of an analytics experiment
Describe how you would set up control and treatment groups, define success metrics, and use statistical significance to determine the effectiveness of a business initiative.

3.1.3 Evaluate an A/B test's sample size.
Explain how you would determine the minimum sample size needed for an experiment, considering power, significance level, and expected effect size.

3.1.4 How would you analyze how the feature is performing?
Discuss your approach to identifying relevant KPIs, segmenting users, and using statistical analysis to assess feature adoption and impact.

3.1.5 How would you design user segments for a SaaS trial nurture campaign and decide how many to create?
Describe how you’d use data-driven criteria (behavioral, demographic, or engagement-based) to define segments and test their effectiveness in driving conversions.

3.2 Data Modeling, Warehousing & ETL

You’ll be expected to design scalable data models and ETL pipelines that support robust analytics and reporting. These questions focus on your technical ability to structure, optimize, and troubleshoot complex data environments.

3.2.1 Design a data warehouse for a new online retailer
Lay out your approach to dimensional modeling, data integration, and supporting evolving business needs with scalable schemas.

3.2.2 Ensuring data quality within a complex ETL setup
Explain strategies for monitoring, validating, and remediating data quality issues in multi-source ETL pipelines.

3.2.3 Write a query to get the current salary for each employee after an ETL error.
Demonstrate your ability to identify and correct data inconsistencies using SQL, ensuring data integrity after errors.

3.2.4 Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners.
Describe your approach to building flexible, reliable pipelines that can handle varied data formats and volumes.

3.2.5 Design an end-to-end data pipeline to process and serve data for predicting bicycle rental volumes.
Walk through your process for data ingestion, transformation, storage, and serving, highlighting automation and reliability.

3.3 Data Visualization & Communication

Clear communication and the ability to make data accessible are critical for Business Intelligence. Expect questions on tailoring insights for diverse audiences and creating impactful dashboards.

3.3.1 How to present complex data insights with clarity and adaptability tailored to a specific audience
Explain your process for distilling technical findings into actionable recommendations and adjusting your presentation style based on stakeholder needs.

3.3.2 Making data-driven insights actionable for those without technical expertise
Discuss how you translate analytical results into straightforward, business-relevant messages.

3.3.3 Demystifying data for non-technical users through visualization and clear communication
Share your strategies for designing dashboards and reports that empower decision-making across functions.

3.3.4 Which metrics and visualizations would you prioritize for a CEO-facing dashboard during a major rider acquisition campaign?
Describe your approach to selecting high-level KPIs and visual formats that align with executive priorities.

3.3.5 How would you visualize data with long tail text to effectively convey its characteristics and help extract actionable insights?
Explain techniques for summarizing and displaying large, unstructured datasets to surface key trends.

3.4 Data Quality & Cleaning

Maintaining high data quality is foundational for accurate analysis. These questions assess your ability to identify, clean, and document data issues in real-world scenarios.

3.4.1 Describing a real-world data cleaning and organization project
Outline the steps you take to profile, clean, and validate large or messy datasets, and how you communicate limitations.

3.4.2 Challenges of specific student test score layouts, recommended formatting changes for enhanced analysis, and common issues found in "messy" datasets.
Discuss your approach to restructuring data for analysis, including normalization, error checking, and automation.

3.4.3 How would you approach improving the quality of airline data?
Describe data profiling, root cause analysis, and the implementation of quality controls in recurring ETL processes.

3.4.4 Write a query to get the current salary for each employee after an ETL error.
Explain how to identify and resolve discrepancies, ensuring data accuracy for business reporting.

3.4.5 How would you determine which database tables an application uses for a specific record without access to its source code?
Discuss your investigative approach using metadata, logs, and query analysis to trace data lineage.

3.5 Behavioral Questions

3.5.1 Tell me about a time you used data to make a decision.
Describe a scenario where your analysis directly impacted a business outcome, emphasizing the metrics you tracked and the communication of your recommendation.

3.5.2 Describe a challenging data project and how you handled it.
Share the complexities involved, how you overcame obstacles, and the final impact of your work.

3.5.3 How do you handle unclear requirements or ambiguity?
Explain your process for clarifying objectives, asking the right questions, and iterating on solutions when project goals are not fully defined.

3.5.4 Tell me about a time when your colleagues didn’t agree with your approach. What did you do to bring them into the conversation and address their concerns?
Discuss your communication and collaboration strategies, and how you achieved consensus or compromise.

3.5.5 Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?
Share how you adapted your message or approach to bridge understanding gaps and move the project forward.

3.5.6 Describe a time you had to negotiate scope creep when two departments kept adding “just one more” request. How did you keep the project on track?
Explain how you managed competing priorities, set boundaries, and maintained project integrity.

3.5.7 When leadership demanded a quicker deadline than you felt was realistic, what steps did you take to reset expectations while still showing progress?
Detail how you communicated risks, re-prioritized deliverables, and ensured transparency with stakeholders.

3.5.8 Give an example of how you balanced short-term wins with long-term data integrity when pressured to ship a dashboard quickly.
Describe the tradeoffs you made, safeguards you implemented, and how you communicated limitations to leadership.

3.5.9 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Highlight your persuasion tactics, use of evidence, and ability to drive alignment.

3.5.10 Walk us through how you handled conflicting KPI definitions (e.g., “active user”) between two teams and arrived at a single source of truth.
Discuss your process for facilitating agreement, documenting definitions, and ensuring consistency across reporting.

4.1 Company-specific tips:

Familiarize yourself with the unique challenges and priorities of the utility sector, especially as they relate to energy delivery, infrastructure modernization, and regulatory compliance at Southern California Edison. Understand SCE’s mission to provide reliable and sustainable energy, and be prepared to discuss how business intelligence can drive operational efficiency and customer satisfaction within a highly regulated environment.

Research recent SCE initiatives around grid modernization, renewable energy integration, and customer service improvements. Be ready to reference these in your answers and demonstrate how your analytical skills can support SCE’s push for innovation and sustainability.

Develop a working knowledge of the metrics and KPIs that matter most to SCE’s business, such as outage frequency, energy consumption trends, grid reliability, and customer experience scores. Show that you can connect data analysis to tangible business outcomes that align with SCE’s strategic objectives.

Be prepared to discuss how you would adapt your communication style for both technical and non-technical stakeholders, as SCE values the ability to bridge the gap between data teams and business units. Practice explaining complex findings in a way that is accessible and actionable for leadership, field operations, and customer-facing teams.

4.2 Role-specific tips:

Demonstrate your expertise in data modeling, ETL pipeline design, and data warehousing by preparing to walk through real-world examples of how you’ve structured scalable data environments. For SCE, emphasize your ability to integrate data from disparate systems—such as grid sensors, customer databases, and regulatory reporting tools—to enable holistic analysis and reporting.

Showcase your ability to clean, validate, and maintain high data quality in large, messy, or multi-source datasets. Prepare to discuss your step-by-step approach to profiling data, resolving inconsistencies, and implementing automated quality controls, especially in the context of mission-critical reporting for a utility.

Highlight your experience with dashboard development and data visualization tools like Power BI or Tableau. Be ready to describe how you select metrics, design intuitive layouts, and tailor dashboards for different audiences—executives, field teams, or regulatory bodies—ensuring that insights are not just available, but truly actionable.

Prepare for scenario-based questions involving experimentation, such as how you would design an A/B test to evaluate a new customer program or operational initiative. Practice outlining your process for defining control and treatment groups, selecting relevant KPIs (e.g., customer retention, energy savings), and interpreting results to guide business decisions.

Anticipate questions about stakeholder management and communication. Prepare stories that illustrate your ability to clarify ambiguous requirements, negotiate priorities when faced with scope creep, and build consensus around data definitions or project direction. SCE values professionals who can navigate complex, cross-functional environments with diplomacy and clarity.

Finally, be ready to discuss how you balance the need for quick business wins with the importance of long-term data integrity. Share examples of how you’ve delivered rapid insights or dashboards without sacrificing quality, and how you communicate limitations or risks to leadership to maintain transparency and trust.

5.1 “How hard is the Southern California Edison Business Intelligence interview?”
The SCE Business Intelligence interview is challenging and comprehensive, designed to assess both your technical expertise and your ability to communicate insights effectively to diverse stakeholders. You’ll be evaluated on your data analysis skills, experience with BI tools, understanding of utility operations, and your ability to solve real-world business problems. The process is rigorous, but thorough preparation and a clear understanding of SCE’s mission will set you up for success.

5.2 “How many interview rounds does Southern California Edison have for Business Intelligence?”
Typically, the SCE Business Intelligence interview process includes 4 to 5 rounds: an initial application and resume review, a recruiter screen, one or more technical/case/skills interviews, a behavioral interview, and a final onsite or virtual round with cross-functional stakeholders. Each stage is carefully structured to evaluate both your technical and interpersonal capabilities.

5.3 “Does Southern California Edison ask for take-home assignments for Business Intelligence?”
While SCE’s interview process is primarily focused on live technical and case interviews, some candidates may be asked to complete a take-home assignment or technical assessment. This could involve analyzing a dataset, designing a dashboard, or proposing a solution to a business scenario relevant to the energy sector.

5.4 “What skills are required for the Southern California Edison Business Intelligence?”
Key skills include advanced proficiency in SQL, data modeling, ETL pipeline design, and dashboard development (using tools like Power BI or Tableau). Strong analytical and problem-solving abilities, experience with data cleaning and validation, and the ability to communicate complex insights to both technical and non-technical audiences are essential. Familiarity with utility operations, regulatory requirements, and customer-centric metrics is highly valued.

5.5 “How long does the Southern California Edison Business Intelligence hiring process take?”
The typical SCE Business Intelligence hiring process takes between 3 to 5 weeks from application to offer. Timelines may vary depending on candidate availability and scheduling logistics, but SCE’s recruiting team aims to keep the process efficient and transparent, with most technical and onsite rounds scheduled within a week of each other.

5.6 “What types of questions are asked in the Southern California Edison Business Intelligence interview?”
You can expect a mix of technical, case-based, and behavioral questions. Technical questions often cover data analysis, SQL queries, ETL pipeline design, data warehousing, and dashboard development. Case questions may involve designing experiments, interpreting business scenarios, or solving data quality challenges. Behavioral questions will assess your communication skills, stakeholder management, and alignment with SCE’s values and mission.

5.7 “Does Southern California Edison give feedback after the Business Intelligence interview?”
SCE typically provides feedback through the recruiter, especially if you progress to later stages. While detailed technical feedback may be limited, you can expect high-level insights on your performance and, if not selected, constructive guidance for future opportunities.

5.8 “What is the acceptance rate for Southern California Edison Business Intelligence applicants?”
While specific acceptance rates are not publicly disclosed, Business Intelligence roles at SCE are highly competitive due to the technical demands and the impact these positions have on the organization. Only a small percentage of applicants advance through all interview rounds to receive an offer.

5.9 “Does Southern California Edison hire remote Business Intelligence positions?”
SCE offers some flexibility for remote or hybrid work arrangements for Business Intelligence roles, depending on team needs and project requirements. Certain positions may require on-site presence for collaboration or access to secure systems, but remote options are increasingly available, especially for highly qualified candidates.

• Related guides:
  • Southern California Edison interview questions
  • Business Intelligence interview guide
  • Top Business Intelligence interview tips
  • Top 12 Business Intelligence Case Studies
  • How to Prepare for Business Intelligence Interviews: Success Story

Ready to ace your Southern California Edison Business Intelligence interview? It’s not just about knowing the technical skills—you need to think like a Southern California Edison Business Intelligence professional, solve problems under pressure, and connect your expertise to real business impact. That’s where Interview Query comes in with company-specific learning paths, mock interviews, and curated question banks tailored toward roles at Southern California Edison and similar companies.

With resources like the Southern California Edison Business Intelligence Interview Guide and our latest case study practice sets, you’ll get access to real interview questions, detailed walkthroughs, and coaching support designed to boost both your technical skills and domain intuition.

Take the next step—explore more case study questions, try mock interviews, and browse targeted prep materials on Interview Query. Bookmark this guide or share it with peers prepping for similar roles. It could be the difference between applying and offering. You’ve got this!