Ey Business Intelligence Interview Guide

Getting ready for a Business Intelligence interview at EY? The EY Business Intelligence interview process typically spans several question topics and evaluates skills in areas like data modeling, SQL, analytics, data visualization, and stakeholder communication. Interview preparation is especially important for this role at EY, as candidates are expected to demonstrate not only technical expertise but also the ability to translate complex data into actionable insights that drive business decisions and align with EY’s commitment to client success and operational excellence.

In preparing for the interview, you should:

• Understand the core skills necessary for Business Intelligence positions at EY.
• Gain insights into EY’s Business Intelligence interview structure and process.
• Practice real EY 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 EY Business Intelligence interview process, along with sample questions and preparation tips tailored to help you succeed.

EY (Ernst & Young) is a global leader in assurance, tax, transaction, and advisory services, supporting clients in building trust and confidence in capital markets and economies worldwide. Through its network of member firms, EY delivers high-quality insights and solutions to businesses, governments, and communities, helping to address complex challenges and drive sustainable growth. The company is committed to developing outstanding leaders and fostering a culture of integrity and collaboration. As a Business Intelligence professional at EY, you will contribute to delivering data-driven insights that support clients’ strategic decision-making and EY’s mission of building a better working world.

As a Business Intelligence professional at EY, you will be responsible for transforming complex data into actionable insights that inform strategic business decisions for clients and internal teams. Your core tasks include gathering and analyzing large datasets, developing interactive dashboards, and creating visualizations to communicate key findings. You will collaborate with consultants, data engineers, and business stakeholders to identify trends, optimize processes, and support data-driven recommendations. This role is integral to helping EY’s clients improve operational efficiency, drive growth, and maintain a competitive edge through informed decision-making.

2.1 Stage 1: Application & Resume Review

The process at EY for Business Intelligence roles begins with an initial screening of your application and resume. Recruiters and hiring managers look for demonstrated expertise in SQL and analytics, strong experience with data modeling, and evidence of presenting actionable insights. Highlight your proficiency in designing and implementing BI solutions, as well as your ability to communicate findings to stakeholders. Ensure your resume clearly showcases relevant project experience, technical skills, and business impact.

2.2 Stage 2: Recruiter Screen

Following resume review, you can expect a recruiter call that lasts around 30 minutes. This conversation typically assesses your motivation for joining EY, your communication skills (often including English proficiency), and an overview of your experience with BI tools and technologies. Be prepared to articulate why you are interested in EY specifically and how your background aligns with their business intelligence needs. Preparation should focus on succinctly summarizing your experience and practicing responses to common motivational and fit questions.

2.3 Stage 3: Technical/Case/Skills Round

The technical interview round, often conducted online, is designed to evaluate your hands-on skills in SQL, analytics, and BI system design. You may be asked to discuss previous data projects, explain models you have implemented, and walk through your approach to solving business problems with data. Expect in-depth questions about data warehousing, ETL processes, dashboard creation, and data visualization strategies. Preparation should include reviewing your technical portfolio, practicing explanations of complex projects, and brushing up on advanced SQL and analytical concepts.

2.4 Stage 4: Behavioral Interview

Behavioral interviews at EY for BI roles focus on assessing your collaboration skills, adaptability, and ability to present insights to both technical and non-technical audiences. Interviewers may explore how you have managed project challenges, worked within cross-functional teams, and ensured data quality in complex environments. Prepare by reflecting on your experiences with stakeholder communication, handling setbacks, and tailoring presentations for different audiences.

2.5 Stage 5: Final/Onsite Round

The final stage often involves multiple interviews with BI team leads, analytics directors, and other stakeholders. These sessions can include both technical case studies and behavioral scenarios, requiring you to demonstrate your end-to-end BI solutioning skills and business acumen. You may be asked to present previous work, solve real-world business problems, and discuss your approach to data-driven decision making. Preparation should focus on structuring clear, impactful presentations and being ready to answer follow-up questions about your methodologies and results.

2.6 Stage 6: Offer & Negotiation

Once you successfully complete the interview rounds, the recruiter will reach out to discuss your offer package, including compensation, benefits, and potential team placement. This step may also involve negotiation on start date and role specifics. Preparation here includes researching industry benchmarks for BI roles and prioritizing your preferences for the offer discussion.

2.7 Average Timeline

The typical EY Business Intelligence interview process spans 3-5 weeks from initial application to offer, with most candidates experiencing 3-4 interview rounds. Fast-track candidates with highly relevant experience may progress in as little as 2-3 weeks, while standard pacing allows about a week between each stage. Onsite or final rounds may be scheduled flexibly depending on the availability of team leads and directors.

Next, let’s break down the types of interview questions you can expect at each stage.

3.1 SQL & Data Analytics

For Business Intelligence roles at EY, expect to demonstrate advanced SQL skills and analytical thinking applied to real-world business scenarios. You should focus on writing efficient queries, handling diverse datasets, and translating raw data into actionable insights for stakeholders. Be ready to discuss your decision-making process and how you validate data quality.

3.1.1 Write a SQL query to count transactions filtered by several criterias.
Clarify the filtering criteria, use WHERE clauses to select relevant records, and aggregate using COUNT. Mention how you would optimize for performance with large datasets.

3.1.2 Create a new dataset with summary level information on customer purchases.
Outline your approach to aggregating purchase data by customer, selecting key metrics like total spend or frequency, and discuss how summary tables can drive business decisions.

3.1.3 You’re tasked with analyzing data from multiple sources, such as payment transactions, user behavior, and fraud detection logs. How would you approach solving a data analytics problem involving these diverse datasets? What steps would you take to clean, combine, and extract meaningful insights that could improve the system's performance?
Explain your data cleaning, normalization, and joining strategy. Highlight how you ensure consistency and integrity when merging heterogeneous data.

3.1.4 Write a query to get the current salary for each employee after an ETL error.
Describe how you would identify and correct anomalies using SQL, possibly by joining with backup tables or using window functions to track changes.

3.1.5 Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners.
Discuss the architecture, data validation, and transformation stages. Emphasize how you would ensure data quality and scalability in a BI context.

3.2 Data Modeling & Warehousing

EY Business Intelligence professionals are expected to design robust data models and warehouses that support business growth and analytics needs. Focus on your ability to structure data for efficient querying, scalability, and reporting.

3.2.1 Design a data warehouse for a new online retailer.
Describe your approach to schema design, fact and dimension tables, and how you would support business reporting requirements.

3.2.2 How would you design a data warehouse for a e-commerce company looking to expand internationally?
Discuss handling localization, currency, and regulatory requirements in your warehouse design. Explain how you’d ensure flexibility for future expansion.

3.2.3 Design a dashboard that provides personalized insights, sales forecasts, and inventory recommendations for shop owners based on their transaction history, seasonal trends, and customer behavior.
Explain your process for selecting metrics, visualizations, and personalization logic. Emphasize stakeholder collaboration and iterative design.

3.2.4 System design for a digital classroom service.
Outline key components, data flows, and how you would support analytics for educators and administrators.

3.2.5 Design a database for a ride-sharing app.
Describe tables, relationships, and how you would optimize for reporting on user activity and operational metrics.

3.3 Data Quality & Cleaning

Ensuring data integrity and quality is crucial for BI at EY. You’ll need to demonstrate your ability to identify, clean, and prevent data issues, especially in complex ETL environments.

3.3.1 Ensuring data quality within a complex ETL setup.
Discuss your approach to monitoring, validating, and reconciling data across multiple sources and transformations.

3.3.2 Describing a real-world data cleaning and organization project.
Share your process for profiling, cleaning, and documenting steps, including communication with stakeholders about limitations.

3.3.3 How would you approach improving the quality of airline data?
Explain how you would identify common data issues, implement automated checks, and measure improvement over time.

3.3.4 Challenges of specific student test score layouts, recommended formatting changes for enhanced analysis, and common issues found in "messy" datasets.
Describe strategies for normalizing and restructuring data, and how to communicate these changes to non-technical users.

3.3.5 Write a function to return the cumulative percentage of students that received scores within certain buckets.
Detail your approach to binning data, calculating percentages, and visualizing results for stakeholders.

3.4 Business Impact & Experimentation

EY values BI professionals who can measure and communicate the business impact of their analyses. Expect questions on experimentation, metric selection, and actionable recommendations.

3.4.1 The role of A/B testing in measuring the success rate of an analytics experiment.
Describe how you would design, implement, and interpret an A/B test in a business context.

3.4.2 Evaluate an A/B test's sample size.
Discuss how you would calculate required sample sizes and assess statistical power for reliable results.

3.4.3 *We're interested in how user activity affects user purchasing behavior. *
Explain your approach to cohort analysis, correlation, and presenting actionable recommendations.

3.4.4 Which metrics and visualizations would you prioritize for a CEO-facing dashboard during a major rider acquisition campaign?
Justify your choices of KPIs, visualization types, and how you would tailor insights for executive decision-making.

3.4.5 How would you analyze how the feature is performing?
Walk through defining success metrics, collecting relevant data, and presenting findings to stakeholders.

3.5 Data Visualization & Communication

Clear communication and visualization are essential in EY’s BI roles. You’ll be expected to make complex data accessible and actionable for diverse audiences.

3.5.1 How to present complex data insights with clarity and adaptability tailored to a specific audience
Explain your process for understanding audience needs, choosing relevant visuals, and distilling key messages.

3.5.2 Making data-driven insights actionable for those without technical expertise
Discuss techniques for simplifying jargon, using analogies, and focusing on business value.

3.5.3 Demystifying data for non-technical users through visualization and clear communication
Describe your approach to designing intuitive dashboards and reports that drive adoption.

3.5.4 How would you visualize data with long tail text to effectively convey its characteristics and help extract actionable insights?
Share strategies for summarizing, grouping, and highlighting important patterns in textual data.

3.5.5 What kind of analysis would you conduct to recommend changes to the UI?
Detail your process for user journey mapping, identifying drop-off points, and translating findings into actionable UI recommendations.

3.6 Behavioral Questions

3.6.1 Tell me about a time you used data to make a decision.
Describe the business context, your analysis, and the impact of your recommendation. Highlight how your insights drove measurable change.

3.6.2 Describe a challenging data project and how you handled it.
Share the obstacles you faced, your problem-solving approach, and how you ensured project success.

3.6.3 How do you handle unclear requirements or ambiguity?
Explain your strategy for clarifying objectives, iterative communication, and adapting your analysis as new information emerges.

3.6.4 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 how you facilitated dialogue, presented evidence, and worked towards consensus.

3.6.5 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?
Outline your prioritization framework, communication tactics, and how you maintained project integrity.

3.6.6 When leadership demanded a quicker deadline than you felt was realistic, what steps did you take to reset expectations while still showing progress?
Share how you communicated risks, adjusted deliverables, and kept stakeholders informed.

3.6.7 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Describe your approach to building trust, presenting compelling evidence, and driving alignment.

3.6.8 Describe how you prioritized backlog items when multiple executives marked their requests as “high priority.”
Explain the frameworks you used and how you communicated trade-offs.

3.6.9 You’re given a dataset that’s full of duplicates, null values, and inconsistent formatting. The deadline is soon, but leadership wants insights from this data for tomorrow’s decision-making meeting. What do you do?
Discuss your triage strategy, balancing speed and rigor, and how you communicate data caveats.

3.6.10 Share a story where you used data prototypes or wireframes to align stakeholders with very different visions of the final deliverable.
Explain how you facilitated alignment through rapid prototyping and iterative feedback.

4.1 Company-specific tips:

EY places a premium on professionalism, integrity, and a consultative mindset. Before your interview, immerse yourself in EY’s business model, core values, and recent initiatives in advisory and analytics. Understand how EY leverages data to drive strategic decisions for clients in diverse industries, from finance to technology to government. Be prepared to articulate how your BI skills align with EY’s mission to build a better working world, and reference real-world examples of EY’s impact where possible.

Demonstrate your understanding of EY’s client-centric approach by researching their typical engagements, such as digital transformation, risk management, and operational excellence projects. Be ready to discuss how BI solutions can enable these outcomes and support clients in navigating complex business challenges. Highlight your ability to work collaboratively in cross-functional teams, reflecting EY’s emphasis on teamwork and leadership development.

Showcase your awareness of EY’s commitment to data privacy and regulatory compliance. Familiarize yourself with global data governance trends and be prepared to discuss how you ensure compliance and ethical data use in BI projects. This will position you as a candidate who can uphold EY’s reputation for trust and integrity in client relationships.

4.2 Role-specific tips:

Highlight your expertise in designing and implementing scalable BI solutions, especially those involving complex data modeling, ETL pipelines, and interactive dashboards. Prepare to discuss how you’ve transformed raw data into actionable insights that influenced business decisions. Reference specific tools you’ve used—such as SQL, Power BI, Tableau, or similar platforms—and explain how you tailored your approach to meet stakeholder needs.

Be ready to walk through your process for cleaning, organizing, and validating data in challenging environments. EY values candidates who can maintain data quality across diverse sources, so prepare examples of how you’ve handled messy datasets, resolved inconsistencies, and communicated limitations to non-technical users. Emphasize your ability to balance speed and rigor when deadlines are tight, and describe strategies for triaging data issues under pressure.

Demonstrate your analytical acumen by discussing how you select key metrics, design experiments (such as A/B tests), and measure business impact. Prepare to explain your approach to cohort analysis, dashboard design, and presenting insights to executive audiences. Show that you can translate complex findings into clear, actionable recommendations that drive measurable results.

Practice your communication skills, especially in presenting data-driven insights to both technical and non-technical stakeholders. EY values BI professionals who can make data accessible and actionable, so rehearse how you simplify jargon, use analogies, and focus on business value. Be ready to share examples of how you’ve facilitated alignment and adoption of BI solutions across diverse teams.

Finally, reflect on your experiences with stakeholder management, ambiguity, and negotiation. Prepare stories that showcase your ability to clarify requirements, prioritize competing requests, and influence without formal authority. EY looks for BI professionals who are adaptable, resilient, and able to drive consensus in complex environments.

By internalizing these tips and approaching your EY Business Intelligence interview with confidence and clarity, you’ll position yourself as a standout candidate ready to make an impact. Remember, every question is an opportunity to showcase your technical expertise, business acumen, and collaborative spirit—qualities that define success at EY. Good luck, and go show them the value you bring!

5.1 How hard is the EY Business Intelligence interview?
The EY Business Intelligence interview is considered moderately challenging, especially for candidates who haven’t previously worked in a consulting environment or with enterprise-scale BI solutions. You’ll be assessed on your ability to model complex data, build scalable ETL pipelines, and communicate insights to both technical and business stakeholders. EY’s focus on professionalism and client impact means you’ll need to demonstrate not just technical skills, but also consultative thinking and adaptability. Candidates who prepare with real-world BI scenarios and practice stakeholder communication tend to perform best.

5.2 How many interview rounds does EY have for Business Intelligence?
Typically, the EY Business Intelligence interview process includes 4-5 rounds: an initial recruiter screen, a technical or case interview, a behavioral interview, and a final onsite or virtual round with BI leads and directors. Some candidates may also complete a take-home assignment or technical assessment, depending on the team and location. Each round is designed to evaluate different aspects of your BI expertise and consulting fit.

5.3 Does EY ask for take-home assignments for Business Intelligence?
EY sometimes includes a take-home assignment or technical case study as part of the Business Intelligence interview process. These assignments usually involve analyzing a dataset, designing a dashboard, or solving a business problem using BI tools. The goal is to assess your practical skills in data analysis, visualization, and storytelling. Be prepared to present your findings and explain your methodology clearly.

5.4 What skills are required for the EY Business Intelligence?
EY expects Business Intelligence candidates to have strong SQL and data modeling skills, experience with ETL pipelines, and proficiency in BI tools such as Power BI, Tableau, or Qlik. Analytical thinking, data visualization, and stakeholder communication are crucial. You should also be comfortable with data cleaning, warehousing concepts, and presenting actionable insights to drive business outcomes. Consulting skills—such as problem-solving, adaptability, and professionalism—are highly valued.

5.5 How long does the EY Business Intelligence hiring process take?
The typical EY Business Intelligence hiring process takes between 3 and 5 weeks from application to offer. This timeline can vary based on candidate availability, team schedules, and the complexity of the interview rounds. Fast-track candidates may complete the process in as little as 2-3 weeks, while others may experience longer gaps between stages.

5.6 What types of questions are asked in the EY Business Intelligence interview?
Expect a mix of technical and behavioral questions. Technical questions cover SQL queries, data modeling, ETL design, dashboard creation, and data quality challenges. You may be asked to solve real-world business scenarios, analyze messy datasets, or design BI solutions for clients. Behavioral questions focus on collaboration, stakeholder management, adaptability, and consulting mindset. Be ready to discuss how you’ve influenced decisions, handled ambiguity, and communicated insights to diverse audiences.

5.7 Does EY give feedback after the Business Intelligence interview?
EY typically provides high-level feedback through recruiters, especially if you reach the final stages. While detailed technical feedback may be limited, you’ll often receive insights into your interview performance and areas for improvement. The feedback process is professional and focused on helping candidates understand their fit for the role.

5.8 What is the acceptance rate for EY Business Intelligence applicants?
While EY does not publicly disclose acceptance rates, the Business Intelligence role is competitive, with an estimated 5-8% acceptance rate for qualified applicants. Candidates who demonstrate both technical expertise and consulting acumen stand out in the selection process.

5.9 Does EY hire remote Business Intelligence positions?
Yes, EY offers remote and hybrid positions for Business Intelligence professionals, depending on the team and project requirements. Some client-facing roles may require occasional travel or onsite collaboration, but EY has embraced flexible work arrangements to attract top BI talent globally. Be sure to clarify remote options during your interview process.

• Related guides:
  • EY interview questions
  • Business Intelligence interview guide
  • Top Business Intelligence interview tips
  • Business Intelligence Career Path: How to Get Started + Tips

Ready to ace your EY Business Intelligence interview? It’s not just about knowing the technical skills—you need to think like an EY 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 EY and similar companies.

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