ING Data Engineer interview questions & guide 2026

The questions below represent common patterns observed in ING interviews. While the specific technical focus may shift depending on the team’s current project, the goal remains to assess your practical problem-solving skills and your ability to navigate the ING ecosystem.

Technical and Domain Expertise

These questions test your foundational knowledge of data systems and your experience with banking-specific data challenges.

• How do you optimize ETL processes for large-scale data warehousing?
• Can you explain your experience with data modeling in a complex banking environment?

Preparation at ING should be focused on demonstrating both depth of technical knowledge and the ability to operate within a highly collaborative, international framework. Focus your preparation on these key evaluation criteria:

Role-related knowledge – You must demonstrate proficiency in ETL processes, Data Modeling, and Cloud environments (specifically Azure). Be prepared to discuss how you apply these technologies to solve real-world problems in the finance sector.

Problem-solving ability – Interviewers look for candidates who don't just follow instructions but analyze the business need behind the technical request. Structure your answers using the STAR method (Situation, Task, Action, Result) to show how you navigate challenges.

Leadership and Influence – Even in technical roles, ING values leadership. You should be able to articulate how you communicate technical solutions to non-technical stakeholders and how you advocate for best practices within your team.

Culture fit / Values – You are expected to embody the Orange Code, which includes accountability, a positive attitude, and a commitment to diversity and inclusion. Show that you are comfortable with change and eager to learn in an Agile setting.

The interview process at ING is designed to be efficient but thorough, typically consisting of four distinct stages. You will start with an initial conversation with an HR representative to discuss your background, motivations, and logistical fit. If successful, you will move through a technical assessment—either an online test or a coding challenge—followed by a review session to discuss your results and design approach.

The final stages involve discussions with team leads or hiring managers. Throughout this process, expect a mix of technical deep-dives and behavioral interviews. The pace is generally professional and structured, though responsiveness can vary by location. The focus is consistently on your practical application of data engineering principles and your ability to work within the One Agile Way of Working.

The timeline above highlights the progression from initial screening to technical validation and final behavioral assessments. Candidates should use this structure to pace their technical review, ensuring they are prepared for both high-level architecture discussions and hands-on coding. Note that interview formats can vary slightly by region, so maintain flexibility in your preparation.

Technical Proficiency

This is the core of the assessment. You will be evaluated on your ability to handle data lifecycle management, from ingestion to reporting. Strong performance means you can explain not just how you used a tool, but why it was the best choice for that specific scenario.

Be ready to go over:

• Data Architecture – Designing scalable data lakes and warehouses.
• ETL Optimization – Improving performance in Oracle or BigQuery environments.

As a Data Engineer, your day-to-day will focus on ensuring the sustainability and reliability of ING’s informational platforms. You will be responsible for the end-to-end lifecycle of data, from technical design and development of ETL processes to the final delivery of reporting solutions. You are expected to monitor these processes rigorously, detecting technical issues and searching for solutions that align with the bank's data strategy.

Collaboration is central to this role. You will work within a Scrum Team, connecting daily with other departments to ensure that your data solutions meet the needs of regulatory and analytical teams. You will also participate in the evolution of the technical stack, implementing automation tools and ensuring that all development aligns with Azure DevOps standards and IT risk controls.

A strong candidate for Data Engineer at ING is someone who balances technical depth with a proactive, "can-do" mindset. You should be prepared to demonstrate that you can work independently while contributing to a wider international team.

Must-have skills:

• Proficiency in SQL and NoSQL databases.
• Hands-on experience with ETL processes and BI Reporting.
• Proven domain experience in data warehousing or data lakes.
• Excellent communication skills in English.
• Experience working in Agile environments.

Nice-to-have skills:

• Experience with cloud environments, particularly Azure.
• Knowledge of big data tools like BigQuery, Oracle 19c, or Denodo.
• Proficiency in automation scripting (e.g., Python, Go, DBT).
• Familiarity with monitoring tools like ELK, Prometheus, or Grafana.

Q: How long does the interview process typically take? The process typically spans a few weeks, depending on the speed of scheduling. From the initial HR screen to the final decision, you can expect a series of 3–4 interactions.

Q: Is there a specific emphasis on coding in the interviews? Yes, you will likely encounter coding or problem-solving tasks. These are designed to test your logic and ability to write clean, maintainable code rather than complex algorithmic puzzles.

Q: What is the culture like at ING? ING values a culture of "Orange Code," which emphasizes being a team player, taking initiative, and being accountable. It is a highly collaborative, international, and fast-paced environment.

Q: How should I prepare for the behavioral questions? Focus on your past experiences where you demonstrated initiative, adaptability, and clear communication. Use the STAR method to ensure your answers are concise and impactful.

• Understand the "Why": When discussing technical choices, always tie them back to business value or risk mitigation. ING interviewers care about the impact of your work.
• Master the Basics: Don't overlook core database concepts. You may be asked about fundamental principles before diving into advanced cloud architecture.
• Show Your Curiosity: Mention your desire to learn new technologies or adapt to new methodologies. The ability to evolve is highly valued.
• Be Transparent: If you don't know an answer, admit it, but explain your process for finding the solution. Honesty is far better than guessing.

The Data Engineer position at ING is a challenging and rewarding opportunity to work at the forefront of financial technology. By focusing on your technical proficiency in ETL and Data Modeling, while simultaneously showcasing your ability to thrive in an Agile and collaborative environment, you can position yourself as a top candidate. Remember that your interviewers are looking for a teammate who is both technically capable and culturally aligned with the Orange Code.

You can explore additional interview insights, practice questions, and preparation resources on Dataford to further refine your approach. Success requires preparation, so take the time to review your past projects and practice articulating your problem-solving process clearly.

The provided salary range reflects a broad spectrum of potential compensation based on global data for similar roles. Candidates should interpret these figures as a guide, noting that actual offers are determined by experience, seniority, location, and specific team requirements within ING.