Criteo Business Intelligence Interview Guide

Getting ready for a Business Intelligence interview at Criteo? The Criteo Business Intelligence interview process typically spans multiple question topics and evaluates skills in areas like SQL, analytics, product metrics, probability, and effective presentation of insights. Interview prep is especially important for this role at Criteo, as candidates are expected to demonstrate strong technical proficiency in querying and analyzing large datasets, as well as the ability to translate complex data into actionable business recommendations within the fast-paced online advertising ecosystem.

Criteo is a global technology company specializing in digital advertising solutions powered by data and machine learning. As a Business Intelligence professional at Criteo, you will be responsible for designing and building data pipelines, developing dashboards, conducting deep-dive analyses on advertising performance, and presenting findings to both technical and non-technical stakeholders. Typical projects involve optimizing campaign metrics, measuring the impact of marketing initiatives, and supporting data-driven decision-making across the business, all while ensuring data accuracy and clarity in reporting.

This guide will help you prepare by outlining the essential skills and knowledge areas Criteo expects from Business Intelligence candidates, providing context on the kinds of problems you’ll tackle, and sharing practical insights to help you excel in your interviews. With the right preparation, you’ll be ready to showcase your expertise and stand out as a top candidate for the role.

Criteo is a global performance marketing technology company specializing in data-driven solutions for e-commerce businesses. Leveraging predictive algorithms and deep insights into consumer behavior, Criteo delivers highly personalized advertisements in real-time, helping clients efficiently engage and convert customers. Operating in 130 countries with over 1,600 employees and 27 offices, Criteo partners with more than 8,500 clients and 11,000 publishers to optimize online advertising and drive sales growth. As a Business Intelligence professional, you will play a key role in harnessing data to enhance campaign effectiveness and support Criteo’s mission to improve online shopping experiences.

As a Business Intelligence professional at Criteo, you will be responsible for transforming data into actionable insights that support strategic decision-making across the company’s digital advertising operations. You will work closely with cross-functional teams, including product, sales, and engineering, to analyze campaign performance, identify trends, and generate reports that drive optimization and growth. Core tasks include developing dashboards, automating data workflows, and presenting findings to stakeholders. This role is key to helping Criteo enhance its data-driven approach, improve client outcomes, and maintain its competitive edge in the performance marketing industry.

2.1 Stage 1: Application & Resume Review

The initial step for a Business Intelligence role at Criteo involves a thorough screening of your application and resume. The recruitment team assesses your experience with SQL, analytics, data visualization, and business metrics such as CPC, CTR, and conversion rates. They look for relevant project work, familiarity with online marketing analytics, and a clear demonstration of problem-solving and presentation skills. To prepare, ensure your resume highlights quantifiable achievements in analytics, business intelligence, and technical toolsets, with tailored keywords that match Criteo’s data-driven environment.

2.2 Stage 2: Recruiter Screen

This stage typically consists of a 30-minute phone or video interview with a recruiter or HR representative. Expect questions about your background, motivation for joining Criteo, and your understanding of the company’s business model. The recruiter will evaluate your communication skills and clarify role expectations, sometimes probing your experience with online advertising metrics. Preparation should focus on articulating your interest in Criteo, connecting your experience to their core business, and demonstrating enthusiasm for analytics in a fast-paced tech setting.

2.3 Stage 3: Technical/Case/Skills Round

The technical assessment is a pivotal part of the Criteo BI interview process, often comprising an online test and/or live technical interviews. You’ll encounter SQL queries, analytics case studies, and questions on product metrics, probability, and algorithms. Tasks may include analyzing datasets, solving business problems with data, and presenting actionable insights. You could also be asked to design dashboards or data warehouses, and perform A/B test analysis. Preparation is best focused on hands-on practice with SQL, understanding online advertising metrics, and being ready to discuss your approach to real-world data analytics scenarios.

2.4 Stage 4: Behavioral Interview

Behavioral interviews are conducted by BI team members, managers, or cross-functional stakeholders. These sessions evaluate your ability to communicate complex insights, collaborate across teams, and navigate challenges in analytics projects. Expect to discuss past experiences involving data cleaning, stakeholder communication, and overcoming hurdles in data projects. You should prepare to share examples that highlight your adaptability, presentation skills, and ability to translate technical findings for non-technical audiences.

2.5 Stage 5: Final/Onsite Round

The final round typically includes a series of on-site or virtual interviews with senior managers, directors, and sometimes cross-functional partners. This stage may feature a case study presentation, where you analyze a provided dataset and present findings using slides. You’ll be assessed on your analytical rigor, business acumen, and ability to communicate insights clearly. The panel may also probe deeper into your approach to product metrics, algorithmic thinking, and your fit with Criteo’s collaborative culture. Preparation should center around structuring clear, impactful presentations and being ready to discuss end-to-end analytics solutions.

2.6 Stage 6: Offer & Negotiation

Once you’ve successfully completed all interview rounds, the recruiter will reach out to discuss your offer. This step involves negotiation on compensation, benefits, and start date. Criteo’s process may require additional reference checks or final HR approvals. Be prepared to articulate your value and negotiate confidently based on market benchmarks and your experience.

2.7 Average Timeline

The Criteo Business Intelligence interview process generally spans 3 to 6 weeks from initial contact to offer. Fast-track candidates with highly relevant experience or internal referrals may progress in as little as 2 to 3 weeks, while standard pacing allows for about a week between each stage, with occasional delays due to team availability or scheduling. Online tests are typically time-bound (20–60 minutes), and case study presentations may be scheduled within a week of technical interviews. Some candidates may experience longer waits between rounds, especially for final management interviews.

Now that you know what to expect at each stage, let’s dive into the types of interview questions you’ll encounter throughout the Criteo BI process.

3.1 Data Analytics & Business Insights

Expect questions that assess your ability to extract, communicate, and apply actionable insights from complex datasets. You should be able to tailor your presentation of findings to different audiences and demonstrate a clear understanding of how data impacts business decisions.

3.1.1 How to present complex data insights with clarity and adaptability tailored to a specific audience
Focus on structuring your explanation to match the audience’s level of technical understanding, highlighting key takeaways, and using visualizations when appropriate. Emphasize business relevance and adaptability.

3.1.2 Making data-driven insights actionable for those without technical expertise
Translate technical findings into practical recommendations, using analogies or simplified visuals to bridge the gap. Show how your insights drive decisions for non-technical stakeholders.

3.1.3 Demystifying data for non-technical users through visualization and clear communication
Choose intuitive charts and focus on storytelling that connects data trends to business value. Keep explanations concise and avoid jargon.

3.1.4 Strategically resolving misaligned expectations with stakeholders for a successful project outcome
Describe how you identified differing priorities, facilitated alignment, and communicated trade-offs to ensure a successful, data-driven outcome.

3.1.5 What kind of analysis would you conduct to recommend changes to the UI?
Discuss using funnel analysis, segmentation, and behavioral metrics to diagnose pain points and propose UI changes for improved user experience.

3.2 Data Warehousing & ETL Design

These questions assess your ability to design, optimize, and maintain scalable data infrastructure, which is critical for robust analytics at Criteo. Be prepared to discuss schema design, ETL processes, and handling heterogeneous data sources.

3.2.1 Design a data warehouse for a new online retailer
Outline your approach to schema design, data modeling, and ETL pipeline setup, considering scalability and future analytics needs.

3.2.2 Ensuring data quality within a complex ETL setup
Describe validation checks, error handling, and monitoring strategies you’d use to maintain data integrity across diverse sources.

3.2.3 How would you design a data warehouse for a e-commerce company looking to expand internationally?
Discuss handling localization, compliance, and scalable architecture to support global analytics.

3.2.4 Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners
Explain modular pipeline design, data normalization, and strategies for managing schema evolution.

3.3 SQL & Data Manipulation

Strong SQL skills are essential for querying, aggregating, and transforming data efficiently. Expect questions that test your ability to write complex queries and process large datasets with accuracy.

3.3.1 Write a SQL query to count transactions filtered by several criterias.
Start by identifying relevant filters, then use aggregation and WHERE clauses to efficiently compute the required counts.

3.3.2 Write a query to calculate the conversion rate for each trial experiment variant
Aggregate trial data, count conversions per variant, and compute conversion rates. Discuss handling nulls and edge cases.

3.3.3 Write a query to compute the average time it takes for each user to respond to the previous system message
Use window functions to align messages and calculate time differences, then aggregate by user.

3.3.4 Write a SQL query to find the average number of right swipes for different ranking algorithms.
Group data by algorithm and calculate averages, ensuring correct filtering and aggregation logic.

3.4 Experimentation & Statistical Analysis

You’ll be expected to design, analyze, and interpret A/B tests and other experiments, ensuring statistical rigor and actionable outcomes. Prepare to discuss metrics, sample sizes, and significance testing.

3.4.1 The role of A/B testing in measuring the success rate of an analytics experiment
Explain experiment design, control vs. treatment setup, and how you interpret results to drive business decisions.

3.4.2 Evaluate an A/B test's sample size.
Discuss statistical power, minimum detectable effect, and how you determine if your sample size is sufficient.

3.4.3 Precisely ascertain whether the outcomes of an A/B test, executed to assess the impact of a landing page redesign, exhibit statistical significance.
Describe hypothesis testing, p-values, and confidence intervals, and how you communicate findings to stakeholders.

3.4.4 An A/B test is being conducted to determine which version of a payment processing page leads to higher conversion rates. You’re responsible for analyzing the results. How would you set up and analyze this A/B test? Additionally, how would you use bootstrap sampling to calculate the confidence intervals for the test results, ensuring your conclusions are statistically valid?
Outline your approach to experiment setup, analysis, and using bootstrap methods for robust inference.

3.5 Data Cleaning & Quality Assurance

Criteo values analysts who can handle messy, real-world data and ensure reliability of insights. You’ll be asked about your process for cleaning, profiling, and validating datasets.

3.5.1 Describing a real-world data cleaning and organization project
Summarize steps taken to identify issues, clean data, and validate results, emphasizing reproducibility and documentation.

3.5.2 How would you approach improving the quality of airline data?
Discuss profiling, anomaly detection, and iterative refinement to enhance data quality.

3.5.3 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?
Describe your process for data integration, normalization, and extracting actionable insights from disparate sources.

3.6 Behavioral Questions

3.6.1 Tell me about a time you used data to make a decision.
Share a story where your analysis led directly to a business recommendation or change. Highlight the impact and how you communicated your findings.

3.6.2 Describe a challenging data project and how you handled it.
Discuss a complex project, the obstacles you faced, and the strategies you used to overcome them. Focus on problem-solving and collaboration.

3.6.3 How do you handle unclear requirements or ambiguity?
Explain your approach to clarifying goals, asking targeted questions, and iterating with stakeholders to define scope.

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, how you adjusted your approach, and what you learned from the experience.

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, how you communicated trade-offs, and the outcome for the project.

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?
Explain how you managed expectations, communicated risks, and delivered interim results to maintain trust.

3.6.7 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Share your strategy for building consensus, using evidence, and navigating organizational dynamics.

3.6.8 Describe a situation where two source systems reported different values for the same metric. How did you decide which one to trust?
Discuss your approach to data validation, reconciliation, and stakeholder alignment.

3.6.9 How do you prioritize multiple deadlines? Additionally, how do you stay organized when you have multiple deadlines?
Explain your system for tracking priorities, managing time, and communicating status to stakeholders.

3.6.10 Tell me about a time you delivered critical insights even though 30% of the dataset had nulls. What analytical trade-offs did you make?
Describe how you profiled missingness, chose appropriate treatments, and communicated uncertainty in your findings.

4.1 Company-specific tips:

Immerse yourself in Criteo’s business model and core products, focusing on how the company leverages data and machine learning to deliver personalized advertising solutions. Understand the significance of metrics like click-through rate (CTR), cost-per-click (CPC), conversion rates, and how these drive client success in the global e-commerce and digital marketing space.

Review Criteo’s recent innovations in predictive algorithms and real-time ad serving. Be prepared to discuss how data-driven decision-making impacts both advertisers and publishers, and how Criteo’s technology optimizes campaign performance at scale.

Familiarize yourself with Criteo’s collaborative, cross-functional culture. Be ready to demonstrate your ability to communicate complex insights to both technical and non-technical stakeholders, reflecting the company’s emphasis on teamwork and clear, actionable reporting.

4.2 Role-specific tips:

4.2.1 Practice designing and optimizing SQL queries for real-world advertising datasets.
Develop your SQL skills by working with large, messy datasets that mimic the scale and complexity of Criteo’s advertising data. Focus on writing queries that aggregate campaign metrics, calculate conversion rates, and handle multiple filters and joins. Be comfortable using window functions to analyze trends such as user engagement over time or response times to marketing initiatives.

4.2.2 Prepare to present actionable insights tailored to different audiences.
Refine your ability to translate technical findings into clear, business-focused recommendations. Practice summarizing complex analytics in a way that resonates with executives, marketing teams, and product managers. Use intuitive visualizations and storytelling techniques to connect data trends directly to business outcomes, always highlighting the “so what” behind your analysis.

4.2.3 Demonstrate expertise in data warehousing and scalable ETL pipeline design.
Be ready to discuss your approach to designing robust data warehouses and ETL processes that support diverse analytics needs. Emphasize your experience with schema design, data modeling, and modular ETL architecture. Highlight strategies for maintaining data quality, handling heterogeneous sources, and ensuring scalability for global analytics.

4.2.4 Showcase your ability to design and analyze A/B tests with statistical rigor.
Prepare concrete examples of experiments you’ve designed, analyzed, and interpreted. Focus on your understanding of control/treatment setup, sample size calculations, and statistical significance. Be able to explain how you use bootstrap sampling or other robust methods to quantify uncertainty and communicate findings clearly to stakeholders.

4.2.5 Be ready to discuss your process for cleaning and validating messy, real-world data.
Cite specific projects where you tackled data quality issues, integrated multiple data sources, and ensured the reliability of your insights. Explain your approach to profiling datasets, detecting anomalies, and documenting cleaning steps. Show how you balance analytical trade-offs when dealing with incomplete or inconsistent data.

4.2.6 Prepare stories that highlight your business impact and collaboration skills.
Think of examples where your analytics directly influenced business decisions or campaign optimizations. Be ready to discuss how you navigated ambiguous requirements, managed stakeholder expectations, and communicated trade-offs. Emphasize your adaptability, organizational skills, and ability to deliver results in a fast-paced, deadline-driven environment.

4.2.7 Illustrate your approach to resolving data discrepancies and aligning stakeholders.
Share your methodology for reconciling conflicting metrics from different sources, validating data, and facilitating consensus among teams. Highlight your commitment to data integrity and your ability to communicate technical findings in a way that drives alignment and action across departments.

5.1 “How hard is the Criteo Business Intelligence interview?”
The Criteo Business Intelligence interview is considered moderately to highly challenging, especially for those without direct experience in digital advertising analytics. You’ll need to demonstrate strong technical skills in SQL, data warehousing, and statistical analysis, as well as the ability to translate complex data into actionable business recommendations. The process is thorough, with a focus on real-world problem-solving, business acumen, and clear communication—especially when presenting insights to both technical and non-technical stakeholders.

5.2 “How many interview rounds does Criteo have for Business Intelligence?”
Typically, there are 4 to 6 rounds in the Criteo Business Intelligence interview process. This includes 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 that often includes a presentation. Some candidates may also be asked for references or to complete an additional case study.

5.3 “Does Criteo ask for take-home assignments for Business Intelligence?”
Yes, Criteo may include a take-home case study or technical assessment as part of the process, especially for Business Intelligence roles. This assignment often involves analyzing a dataset, solving a business problem, and presenting your findings in a clear and actionable way. The goal is to evaluate your technical proficiency, analytical rigor, and ability to communicate insights effectively.

5.4 “What skills are required for the Criteo Business Intelligence?”
Key skills for Criteo Business Intelligence include advanced SQL for large-scale data manipulation, strong data warehousing and ETL pipeline design, proficiency in statistical analysis (including A/B testing), and expertise in data visualization and dashboarding. You should also have a deep understanding of digital advertising metrics (such as CTR, CPC, and conversion rates), business acumen, and the ability to present complex findings to diverse audiences.

5.5 “How long does the Criteo Business Intelligence hiring process take?”
The typical timeline for the Criteo Business Intelligence hiring process is 3 to 6 weeks from initial application to offer. Fast-track candidates or those with internal referrals may move through the process in as little as 2 to 3 weeks, while scheduling logistics or additional assessments can extend the timeline.

5.6 “What types of questions are asked in the Criteo Business Intelligence interview?”
Expect a mix of technical and behavioral questions. Technical questions cover SQL queries, data warehousing, ETL design, statistical analysis, and experimentation (A/B testing). You’ll also encounter analytics case studies and business problem-solving scenarios. Behavioral questions focus on collaboration, communication, stakeholder management, and your ability to drive business impact through data.

5.7 “Does Criteo give feedback after the Business Intelligence interview?”
Criteo typically provides high-level feedback through recruiters, especially if you reach the later stages of the process. While detailed technical feedback may be limited, you can expect some insights into your performance and next steps.

5.8 “What is the acceptance rate for Criteo Business Intelligence applicants?”
While Criteo does not publish official acceptance rates, the Business Intelligence role is competitive, with an estimated acceptance rate of 3-6% for qualified applicants. Demonstrating strong analytics skills, business understanding, and clear communication can help you stand out.

5.9 “Does Criteo hire remote Business Intelligence positions?”
Yes, Criteo offers remote and hybrid options for Business Intelligence positions, depending on team needs and location. Some roles may require occasional travel or office visits for team collaboration, but remote-friendly positions are increasingly common within the company.

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

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

With resources like the Criteo 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!