Ikea Group Data Engineer Interview Questions + Guide in 2025

Ikea Group is a global leader in home furnishing, dedicated to improving the everyday lives of many people by embracing innovation and sustainability in its products and services.

The Data Engineer role at Ikea involves building, maintaining, and optimizing data platforms and systems that enable effective data consumption across teams within the organization. Key responsibilities include designing and implementing data models and pipelines, ensuring data quality, and collaborating closely with data scientists and analysts to drive the development of data products that support strategic decision-making. A strong emphasis is placed on using modern data processing tools and cloud technologies, particularly Google Cloud Platform, while fostering agile practices and cross-functional teamwork.

Ideal candidates will possess advanced knowledge of SQL, experience with programming languages such as Python, and familiarity with distributed computing frameworks. Additionally, a commitment to Ikea’s core values, a collaborative spirit, and a passion for continuous learning are essential traits that align with the company's mission to remain a data-driven organization.

This guide will help you prepare for your interview by providing insights into the responsibilities and expectations of the Data Engineer role at Ikea, as well as the essential skills and values that the company cherishes.

The interview process for a Data Engineer position at Ikea Group is structured and designed to assess both technical and cultural fit within the organization. It typically consists of several stages, each focusing on different aspects of the candidate's qualifications and alignment with Ikea's values.

1. Initial Contact

The process begins with an initial outreach, often from a recruiter, who may contact candidates via LinkedIn or email. This initial conversation is generally casual and serves to provide basic information about the role while allowing the recruiter to gauge the candidate's interest and fit for the company culture.

2. Video Interview

Following the initial contact, candidates may be invited to participate in a video interview, often conducted through platforms like HireVue. This stage typically involves answering a series of pre-set questions that assess the candidate's motivations for applying to Ikea, their understanding of the company’s values, and their relevant experiences. Candidates should be prepared to discuss their background and how it aligns with the role.

3. Technical Assessment

Candidates who successfully pass the video interview may be required to complete a technical assessment. This task often involves solving a data-related problem or case study that tests the candidate's SQL skills, programming knowledge (particularly in Python), and understanding of data processing pipelines. The assessment is usually submitted within a specified timeframe, and candidates may need to present their solutions in a follow-up discussion.

4. In-Person or Extended Video Interviews

The next stage typically consists of one or more in-depth interviews with the hiring manager and other team members. These interviews focus on the candidate's technical expertise, including their experience with data structures, distributed computing, and cloud services. Behavioral questions are also common, aimed at understanding how candidates handle challenges and work within cross-functional teams. Candidates should be ready to discuss specific projects and their contributions to past roles.

5. Grandparent Interview

If candidates progress further, they may participate in what is referred to as a "grandparent interview." This stage involves meeting with a senior manager or another key stakeholder who is not directly involved in the hiring process. The focus here is on the candidate's long-term ambitions, their understanding of the data field, and how they can contribute to Ikea's goals. This interview is often more conversational and allows candidates to showcase their unique perspectives and aspirations.

6. Final Steps

The final steps may include discussions about salary expectations and potential offers. Candidates should be prepared for a thorough review of their experiences and how they align with Ikea's mission and values. Communication throughout the process can vary, so candidates are encouraged to establish clear channels for follow-up.

As you prepare for your interview, consider the types of questions that may arise during each stage of the process.

Here are some tips to help you excel in your interview.

Embrace the Casual Atmosphere

IKEA promotes a casual and friendly interview environment, so approach your interview with a relaxed demeanor. This will help you connect with your interviewers and showcase your personality. Remember, they value flat hierarchies and open communication, so don’t hesitate to engage in a two-way conversation. Be genuine and let your enthusiasm for the role and the company shine through.

Showcase Your Technical Skills

As a Data Engineer, you will need to demonstrate your proficiency in SQL and programming languages like Python. Prepare to discuss your experience with data processing, cloud services, and modern software development practices. Be ready to tackle technical questions that may involve writing SQL queries or discussing your approach to building data pipelines. Practicing these skills beforehand will give you the confidence to handle any technical challenges during the interview.

Understand IKEA’s Values

IKEA places a strong emphasis on its corporate identity and core values. Familiarize yourself with their mission to create a better everyday life for the many people. Be prepared to articulate how your personal values align with IKEA’s and why you are passionate about contributing to their vision. Expect questions about your motivation for applying to IKEA, so have thoughtful responses ready that reflect your understanding of the company’s culture.

Prepare for Behavioral Questions

Expect a mix of technical and behavioral questions during your interviews. Be ready to share specific examples from your past experiences that demonstrate your problem-solving skills, teamwork, and adaptability. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you clearly convey your contributions and the impact of your work.

Be Ready for Multiple Interview Rounds

The interview process at IKEA can involve several rounds, including HR interviews, technical assessments, and discussions with hiring managers. Stay organized and keep track of your interactions with different interviewers. Since communication can sometimes be delayed, proactively follow up if you haven’t heard back within the expected timeframe. This shows your interest in the position and helps maintain clarity throughout the process.

Highlight Your Collaborative Spirit

IKEA values teamwork and collaboration, especially in cross-functional settings. Be prepared to discuss how you have worked effectively with others in previous roles, particularly in Agile or DevOps environments. Share examples of how you have contributed to team success and how you can bring that collaborative spirit to IKEA.

Prepare for a Grandparent Interview

If you progress to the final stages, you may encounter a "grandparent interview" with a manager from a different team. This is an opportunity to showcase your ambitions and unique qualities. Be ready to discuss your long-term career goals and how you envision contributing to IKEA’s data-driven transformation. This is your chance to stand out, so think about what makes you a "unicorn" in the data engineering field.

Stay Curious and Open to Learning

IKEA encourages continuous learning and development. Express your eagerness to grow within the company and your commitment to staying updated with industry trends and technologies. Share any relevant projects or learning experiences that demonstrate your proactive approach to professional development.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at IKEA. Good luck!

In this section, we’ll review the various interview questions that might be asked during an interview for a Data Engineer position at Ikea Group. The interview process will likely focus on your technical skills, problem-solving abilities, and alignment with Ikea's values and culture. Be prepared to discuss your experience with data processing, SQL, programming languages, and collaborative software engineering practices.

Technical Skills

1. Can you explain the process of ETL (Extract, Transform, Load) and how you have implemented it in your previous projects?

Understanding ETL is crucial for a Data Engineer, as it is a fundamental process in data management.

How to Answer

Discuss your experience with ETL processes, including the tools you used and the challenges you faced. Highlight how you ensured data quality and efficiency in your implementations.

Example

“In my previous role, I implemented an ETL process using Apache Spark. I extracted data from various sources, transformed it to meet business requirements, and loaded it into a data warehouse. I faced challenges with data quality, which I addressed by implementing validation checks at each stage of the process.”

2. How do you handle missing or incomplete data in your datasets?

Handling missing data is a common challenge in data engineering.

How to Answer

Explain your approach to identifying and addressing missing data, including any techniques or tools you use to mitigate its impact on analysis.

Example

“I typically handle missing data by first assessing the extent of the issue. I might use imputation techniques for small gaps or consider removing records if the missing data is significant. I also ensure to document my approach to maintain transparency in the data processing pipeline.”

3. Describe your experience with SQL. What are some complex queries you have written?

SQL is a critical skill for a Data Engineer, and interviewers will want to assess your proficiency.

How to Answer

Provide examples of complex SQL queries you have written, including the purpose of the queries and the results they produced.

Example

“I have extensive experience with SQL, including writing complex queries involving multiple joins and subqueries. For instance, I created a query that aggregated sales data across different regions and time periods, which helped the management team identify trends and make informed decisions.”

4. What programming languages are you proficient in, and how have you applied them in your work?

Programming skills are essential for building data pipelines and processing data.

How to Answer

Discuss the programming languages you are familiar with, particularly Python, and provide examples of how you have used them in data engineering tasks.

Example

“I am proficient in Python and have used it extensively for data manipulation and analysis. For example, I developed a Python script that automated the data cleaning process, significantly reducing the time required for data preparation before analysis.”

5. Can you explain the concept of distributed computing and its importance in data engineering?

Understanding distributed computing is vital for working with large datasets.

How to Answer

Discuss the principles of distributed computing and how they apply to data engineering, particularly in terms of scalability and performance.

Example

“Distributed computing allows for processing large datasets across multiple machines, which enhances performance and scalability. In my previous role, I utilized Apache Spark to process data in a distributed manner, enabling us to handle terabytes of data efficiently.”

Behavioral Questions

1. Describe a challenging project you worked on and how you overcame the obstacles.

This question assesses your problem-solving skills and resilience.

How to Answer

Share a specific project, the challenges you faced, and the steps you took to overcome them.

Example

“I worked on a project where we needed to integrate data from multiple sources with varying formats. The challenge was ensuring data consistency. I organized a series of meetings with stakeholders to clarify requirements and developed a robust data transformation plan that addressed the inconsistencies.”

2. How do you prioritize tasks when working on multiple projects?

Time management is crucial in a fast-paced environment.

How to Answer

Explain your approach to prioritization and how you ensure deadlines are met.

Example

“I prioritize tasks based on their impact on the business and deadlines. I use project management tools to track progress and communicate with my team regularly to adjust priorities as needed. This approach has helped me manage multiple projects effectively without compromising quality.”

3. How do you ensure that your work aligns with the company’s values and goals?

Cultural fit is important at Ikea, and they will want to see your alignment with their values.

How to Answer

Discuss how you incorporate company values into your work and decision-making processes.

Example

“I believe in the importance of collaboration and sustainability, which are core values at Ikea. I ensure my work promotes teamwork by sharing knowledge with colleagues and advocating for sustainable practices in data management, such as optimizing data storage to reduce costs and environmental impact.”

4. Can you give an example of how you have worked in a cross-functional team?

Collaboration is key in a cross-functional environment.

How to Answer

Share your experience working with different teams and how you contributed to achieving common goals.

Example

“I collaborated with data scientists and product managers on a project to develop a new analytics tool. I contributed by building the data pipeline and ensuring that the data was accessible and reliable for analysis. This collaboration resulted in a successful product launch that met user needs.”

5. What motivates you to work in data engineering?

Understanding your motivation helps interviewers gauge your passion for the role.

How to Answer

Share your enthusiasm for data engineering and how it aligns with your career goals.

Example

“I am motivated by the challenge of transforming raw data into actionable insights. I find it rewarding to solve complex problems and contribute to data-driven decision-making that can significantly impact the business.”