Aon Business Intelligence Interview Guide

Getting ready for a Business Intelligence interview at Aon? The Aon Business Intelligence interview process typically spans a range of question topics and evaluates skills in areas like data analysis, dashboard design, data-driven business insights, and stakeholder communication. Excelling in the interview is crucial at Aon, where business intelligence professionals are expected to transform complex data from diverse sources into actionable insights that drive strategic decision-making, efficiency, and innovation across the organization. Given Aon’s focus on delivering analytical solutions for risk, retirement, and health, preparing thoroughly will help you demonstrate your ability to deliver clear, business-focused recommendations within a dynamic, client-oriented environment.

In preparing for the interview, you should:

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

Aon plc (NYSE:AON) is a leading global professional services firm specializing in risk, retirement, and health solutions. With approximately 50,000 colleagues in 120 countries, Aon leverages proprietary data and analytics to deliver insights that help clients reduce volatility and improve business performance. The company is recognized for its expertise in managing complex risks and providing strategic advice. In a Business Intelligence role at Aon, you will contribute to data-driven decision-making, supporting the firm's mission to empower clients with actionable insights.

As a Business Intelligence professional at Aon, you are responsible for transforming complex data into strategic insights that support the company’s risk, retirement, and health solutions. You will gather, analyze, and visualize large datasets to inform decision-making across various business units. Key tasks include developing dashboards, generating reports, and presenting actionable recommendations to stakeholders. You will collaborate with teams such as analytics, consulting, and operations to enhance business performance and drive client value. This role is central to helping Aon optimize processes and deliver data-driven solutions that align with the company’s commitment to empowering results for clients.

2.1 Stage 1: Application & Resume Review

The initial phase involves a careful screening of your resume and application by Aon's HR team. Here, emphasis is placed on your experience with business intelligence tools (such as SQL, data visualization, and ETL processes), your analytical background, and your ability to distill complex information into actionable business insights. Highlighting experience with data-driven decision-making, dashboard creation, and cross-functional collaboration will help your application stand out. Prepare by ensuring your resume clearly demonstrates your technical expertise, project impact, and communication skills relevant to business intelligence.

2.2 Stage 2: Recruiter Screen

This stage typically consists of a phone or video interview with an HR representative. The conversation centers around your motivation for joining Aon, your fit for the business intelligence role, and a high-level overview of your relevant experience. You can expect questions about your career trajectory, interest in Aon, and alignment with company values. Prepare by articulating your reasons for applying, your understanding of Aon's business, and how your skills can add value to their data-driven initiatives.

2.3 Stage 3: Technical/Case/Skills Round

The technical or case interview is usually conducted by a hiring manager or a panel from the business intelligence team. This round evaluates your proficiency in data analysis, SQL querying, dashboard/report design, and your ability to translate raw data into actionable insights. You may be asked to discuss past data projects, explain how you approach data cleaning and integration from multiple sources, or solve a case involving metrics, business health KPIs, or data pipeline designs. Preparation should include reviewing your hands-on experience with BI tools, practicing clear explanations of technical concepts to non-technical audiences, and demonstrating your ability to solve real-world business problems using data.

2.4 Stage 4: Behavioral Interview

This interview, often with the hiring manager or cross-functional stakeholders, focuses on your interpersonal and communication skills, problem-solving approach, and cultural fit within Aon. Expect to discuss your experience working in diverse teams, handling challenges in data projects, and making data accessible to stakeholders. You may be asked to share examples of times you have influenced business decisions through data insights or navigated obstacles in analytics projects. Preparing relevant stories using the STAR method (Situation, Task, Action, Result) will help you provide concise and impactful responses.

2.5 Stage 5: Final/Onsite Round

The final round may be an onsite or extended virtual interview involving multiple team members, including senior leaders or potential collaborators. This stage often blends technical and behavioral elements, with deeper dives into your analytical thinking, business acumen, and ability to communicate complex insights. You might be asked to present a data project, walk through a dashboard you've built, or respond to scenario-based questions about data-driven decision-making and stakeholder management. To prepare, be ready to discuss your end-to-end project experience, communicate clearly with both technical and non-technical audiences, and demonstrate your knowledge of key business intelligence concepts relevant to Aon's goals.

2.6 Stage 6: Offer & Negotiation

Should you reach this stage, you will engage in discussions with HR regarding compensation, benefits, start date, and any other employment terms. It’s important to approach this step with a clear understanding of your market value, desired benefits, and flexibility, as well as to have thoughtful questions prepared about Aon's work environment and professional development opportunities.

2.7 Average Timeline

The typical Aon Business Intelligence interview process spans approximately 2-4 weeks from application to offer, with the standard pace involving a week between each stage. Fast-track candidates with highly relevant experience, strong technical skills, and clear communication abilities may move through the process more quickly, while some stages may take longer depending on scheduling and team availability.

Next, let’s explore the types of interview questions you’re likely to encounter throughout the Aon Business Intelligence interview process.

3.1. Data Modeling & Warehousing

Business intelligence roles at Aon frequently involve structuring, storing, and integrating data for analysis. Expect questions on designing scalable data warehouses, combining complex data sources, and ensuring data integrity for reporting and analytics.

3.1.1 Design a data warehouse for a new online retailer
Explain your approach to schema design, ETL processes, and how you would optimize for analytical queries. Highlight considerations for scalability and integration with business reporting tools.

3.1.2 How would you design a data warehouse for a e-commerce company looking to expand internationally?
Discuss handling regional differences (currency, language, regulations), scalability, and supporting both global and local reporting needs.

3.1.3 Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners.
Describe how you would handle different data formats, ensure data quality, and maintain performance as data volume grows.

3.1.4 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?
Outline your process for data cleaning, normalization, joining disparate datasets, and validating insights for business impact.

3.2. Data Quality & ETL

Maintaining high data quality and robust ETL processes is vital in business intelligence. Questions in this category test your ability to ensure data reliability, address inconsistencies, and automate data pipelines.

3.2.1 Ensuring data quality within a complex ETL setup
Discuss strategies for monitoring, validating, and remediating data issues in multi-step ETL pipelines.

3.2.2 How would you approach improving the quality of airline data?
Explain methods for profiling data, identifying common quality issues, and implementing corrective actions.

3.2.3 Describing a real-world data cleaning and organization project
Walk through a specific example, emphasizing your process for identifying, prioritizing, and resolving data quality problems.

3.2.4 Design an end-to-end data pipeline to process and serve data for predicting bicycle rental volumes.
Lay out the architecture, from data ingestion and cleaning to modeling and serving results for downstream analytics.

3.3. Analytics & Experimentation

Aon values candidates who can design, measure, and interpret experiments to drive business decisions. These questions focus on A/B testing, causal inference, and making analytics actionable.

3.3.1 The role of A/B testing in measuring the success rate of an analytics experiment
Describe how you would structure an experiment, define success metrics, and interpret the results.

3.3.2 How would you establish causal inference to measure the effect of curated playlists on engagement without A/B?
Discuss alternative methodologies (e.g., difference-in-differences, propensity score matching) and the assumptions required for causal inference.

3.3.3 Write a query to calculate the conversion rate for each trial experiment variant
Explain your approach to grouping, aggregating, and calculating conversion rates, including how to handle missing data.

3.3.4 Assessing the market potential and then use A/B testing to measure its effectiveness against user behavior
Illustrate how you would combine market research with experimentation to validate business hypotheses.

3.4. Business Impact & Communication

Effectively communicating insights and making data accessible to stakeholders is a core part of the business intelligence function. You’ll be evaluated on your ability to translate complex findings into actionable recommendations for diverse audiences.

3.4.1 How to present complex data insights with clarity and adaptability tailored to a specific audience
Share your strategy for adjusting technical depth, using visualizations, and connecting insights to business goals.

3.4.2 Making data-driven insights actionable for those without technical expertise
Describe how you simplify findings, draw analogies, and ensure non-technical stakeholders understand and act on your recommendations.

3.4.3 Demystifying data for non-technical users through visualization and clear communication
Discuss your approach to building intuitive dashboards and reports that empower self-service analytics.

3.4.4 How would you visualize data with long tail text to effectively convey its characteristics and help extract actionable insights?
Explain techniques for summarizing, categorizing, and visualizing textual data to highlight trends and outliers.

3.5. Metrics, Reporting & Dashboards

Aon’s business intelligence teams are expected to define, track, and report on key business metrics. These questions test your ability to design dashboards, select impactful KPIs, and ensure that reporting drives action.

3.5.1 Designing a dynamic sales dashboard to track McDonald's branch performance in real-time
Describe your process for selecting metrics, designing visualizations, and ensuring the dashboard is actionable for business users.

3.5.2 Which metrics and visualizations would you prioritize for a CEO-facing dashboard during a major rider acquisition campaign?
Discuss how you would select high-level KPIs, design concise visualizations, and provide context for executive decision-making.

3.5.3 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 approach to user segmentation, predictive analytics, and tailoring dashboard features to different user needs.

3.5.4 User Experience Percentage
Describe how you would define and calculate a user experience metric, and how it could be tracked over time for business improvement.

3.6 Behavioral Questions

3.6.1 Tell me about a time you used data to make a decision.
Focus on a specific example where your analysis led to a measurable business outcome. Highlight your process, the recommendation you made, and the impact it had.

3.6.2 Describe a challenging data project and how you handled it.
Share a story that demonstrates your problem-solving skills, adaptability, and persistence in overcoming obstacles during a complex analytics project.

3.6.3 How do you handle unclear requirements or ambiguity?
Explain your approach to clarifying objectives, iterating on deliverables, and communicating proactively with stakeholders to ensure alignment.

3.6.4 Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?
Describe the communication barriers you faced, steps you took to bridge the gap, and how you ensured mutual understanding.

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?
Detail how you managed competing priorities, communicated trade-offs, and maintained project focus without sacrificing data quality.

3.6.6 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Highlight your ability to build trust, use evidence-based arguments, and tailor your communication to different audiences.

3.6.7 Tell us about a time you caught an error in your analysis after sharing results. What did you do next?
Be honest about the mistake, describe how you identified and corrected it, and emphasize your commitment to transparency and continuous improvement.

3.6.8 Give an example of automating recurrent data-quality checks so the same dirty-data crisis doesn’t happen again.
Share the tools or processes you implemented, the impact on team efficiency, and how it improved overall data reliability.

3.6.9 How have you balanced speed versus rigor when leadership needed a “directional” answer by tomorrow?
Discuss your triage process, how you prioritized critical data issues, and how you communicated uncertainty in your findings.

3.6.10 Share a story where you used data prototypes or wireframes to align stakeholders with very different visions of the final deliverable.
Describe how you leveraged rapid prototyping to clarify requirements, gather feedback, and build consensus before full-scale development.

4.1 Company-specific tips:

Familiarize yourself with Aon's core business domains—risk, retirement, and health—and understand how data analytics drives strategic decision-making in these areas. Review recent Aon initiatives, annual reports, and key business metrics relevant to their client solutions. This will help you contextualize your interview responses and demonstrate your alignment with Aon's mission to empower clients through actionable insights.

Understand the importance of data-driven recommendations in Aon's consulting approach. Prepare to discuss how business intelligence supports risk management, operational efficiency, and client advisory services. Research the types of stakeholders you might interact with at Aon, such as consultants, actuaries, and senior leadership, and be ready to tailor your communication style for each audience.

Stay updated on industry trends impacting Aon, such as regulatory changes, digital transformation in insurance, and advancements in data privacy. Mentioning these topics in your interview will show your awareness of external factors influencing Aon's business and your readiness to adapt BI solutions accordingly.

4.2 Role-specific tips:

4.2.1 Practice designing scalable data warehouses and ETL pipelines for complex, multi-source environments.
Aon’s BI roles often require integrating diverse datasets (e.g., claims, transactions, client portfolios) into unified reporting platforms. Be prepared to discuss your approach to schema design, data normalization, and building robust ETL processes that ensure data quality and scalability. Use examples from your experience to demonstrate how you’ve handled challenges in data integration and pipeline automation.

4.2.2 Demonstrate your ability to clean, combine, and analyze heterogeneous data for actionable business insights.
Expect questions about working with messy or incomplete data, especially when merging information from different systems or departments. Outline your step-by-step process for data cleaning, validation, and transformation. Share stories where your analysis directly improved business performance, such as optimizing a workflow or identifying cost-saving opportunities.

4.2.3 Be ready to design and explain dashboards tailored to different stakeholder needs.
Showcase your experience building dashboards that distill complex metrics into clear, actionable visualizations. Discuss your process for selecting KPIs, choosing the right visualization techniques, and ensuring reports are intuitive for both technical and non-technical users. Mention how you incorporate user feedback to iterate and improve dashboard functionality.

4.2.4 Prepare to discuss your approach to data quality management and automation.
Aon places high value on reliable data for decision-making. Describe how you monitor data quality, implement automated checks, and remediate issues in ETL pipelines. Provide examples of tools or processes you’ve used to prevent recurring data problems and how these solutions improved team efficiency.

4.2.5 Review your knowledge of A/B testing, causal inference, and experimental design.
Business intelligence at Aon often involves measuring the impact of process changes or new client offerings. Be ready to explain how you structure experiments, define success metrics, and interpret results to inform business strategy. If you’ve used alternative causal inference methods (like difference-in-differences or propensity score matching), describe their application and limitations.

4.2.6 Practice communicating complex data insights to stakeholders with varying technical backgrounds.
You’ll need to translate technical findings into business recommendations that resonate with consultants, executives, and clients. Prepare examples of how you’ve adjusted your communication style, used analogies, or built data prototypes to make insights accessible and actionable. Highlight your ability to foster data-driven decision-making across the organization.

4.2.7 Be ready to share stories of navigating ambiguity and managing stakeholder expectations.
Aon values BI professionals who can handle unclear requirements and changing priorities. Use the STAR method to describe times you clarified objectives, negotiated scope, or balanced speed versus rigor under tight deadlines. Emphasize your proactive communication and adaptability in delivering results.

4.2.8 Prepare to discuss how you influence without formal authority and build consensus around data-driven recommendations.
Share examples of how you’ve used evidence-based arguments, rapid prototyping, or iterative feedback to align diverse stakeholders. Focus on your ability to build trust, listen actively, and drive business impact through collaboration.

4.2.9 Review techniques for visualizing and summarizing long-tail textual data.
Aon’s BI teams may need to extract insights from client feedback, claims notes, or survey responses. Explain your approach to categorizing, summarizing, and visualizing textual data to highlight trends, outliers, and actionable patterns for business users.

4.2.10 Be prepared to discuss metrics selection, reporting strategy, and real-time dashboard design.
Show your expertise in defining impactful KPIs, prioritizing metrics for executive dashboards, and ensuring reports drive business action. Use examples to illustrate how you’ve balanced detail with clarity and supported decision-making at different organizational levels.

5.1 How hard is the Aon Business Intelligence interview?
The Aon Business Intelligence interview is moderately challenging, with a strong emphasis on both technical and business acumen. You’ll be expected to demonstrate proficiency in data analysis, dashboard design, and translating complex datasets into actionable business insights. The process also evaluates your communication skills and ability to collaborate with cross-functional teams. Candidates who prepare thoroughly and can showcase real-world impact from their analytics work stand out.

5.2 How many interview rounds does Aon have for Business Intelligence?
Typically, the Aon Business Intelligence interview process consists of 4-6 rounds: an initial recruiter screen, a technical/case interview, a behavioral interview, and a final round with multiple team members or senior leaders. Some candidates may encounter a take-home assignment or additional stakeholder interviews depending on the specific role and location.

5.3 Does Aon ask for take-home assignments for Business Intelligence?
Yes, Aon may include a take-home assignment in the interview process for Business Intelligence roles. These assignments often involve analyzing a dataset, designing a dashboard, or solving a business case relevant to Aon’s domains (risk, retirement, health). The goal is to assess your practical skills in data cleaning, visualization, and generating actionable recommendations.

5.4 What skills are required for the Aon Business Intelligence?
Key skills for Aon Business Intelligence roles include advanced proficiency in SQL, data visualization tools (such as Tableau or Power BI), ETL processes, and business analytics. Strong communication and stakeholder management abilities are essential, as is experience in designing reports and dashboards that drive business decisions. Familiarity with A/B testing, causal inference, and handling heterogeneous data sources will also give you an edge.

5.5 How long does the Aon Business Intelligence hiring process take?
The Aon Business Intelligence hiring process typically takes 2-4 weeks from application to offer. The timeline can vary based on candidate availability, team schedules, and the complexity of the interview stages. Fast-track candidates with highly relevant experience may move through the process more quickly.

5.6 What types of questions are asked in the Aon Business Intelligence interview?
Expect a mix of technical and business-focused questions, including data modeling, ETL pipeline design, data cleaning, dashboard/report creation, and analytics case studies. Behavioral questions will probe your problem-solving approach, communication style, and ability to influence stakeholders. You may also be asked to present a data project or respond to scenario-based business questions.

5.7 Does Aon give feedback after the Business Intelligence interview?
Aon typically provides feedback through their recruiting team. While high-level feedback is common, detailed technical feedback may be limited depending on the stage and interviewer. Candidates are encouraged to ask for specific areas of improvement, especially after technical or case rounds.

5.8 What is the acceptance rate for Aon Business Intelligence applicants?
While specific acceptance rates aren’t publicly available, Business Intelligence roles at Aon are competitive. The estimated acceptance rate is around 3-7% for qualified applicants, reflecting the high standards for technical expertise and business impact.

5.9 Does Aon hire remote Business Intelligence positions?
Yes, Aon offers remote and hybrid options for Business Intelligence roles, depending on the team and region. Some positions may require occasional in-office collaboration or client meetings, but flexible work arrangements are increasingly common at Aon.

• Related guides:
  • Aon interview questions
  • Business Intelligence interview guide
  • Top Business Intelligence interview tips

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