ING Data Analyst interview questions & guide 2026

Success at ING requires a balanced approach. You must demonstrate technical mastery while proving that you can thrive within a collaborative, fast-paced banking environment.

Role-related knowledge – You must be comfortable with SQL and Python as your primary tools. Interviewers look for evidence that you understand the end-to-end data pipeline, from raw data extraction to final presentation.

Problem-solving ability – ING values structured thinking. When presented with a case study, focus on defining the problem clearly, identifying necessary data points, and proposing a scalable, actionable solution.

Communication and Influence – Your ability to influence stakeholders is just as important as your coding skills. Practice articulating the "so what" behind your data—always explain how your analysis drives business value.

Culture fit and Values – Be prepared to show "courage" and "sincerity." ING culture encourages open feedback and direct communication; demonstrate that you are a team player who takes ownership of their work.

The interview process at ING is generally professional, structured, and aimed at assessing both your technical caliber and your alignment with the team. You can expect a multi-stage process that begins with a recruiter screening, followed by technical assessments—often involving SQL or Python—and concluding with interviews with hiring managers or Chapter Leads.

The pace of the process can vary by location, but it is typically marked by clear communication regarding the next steps. Whether you are interviewing for a role in Amsterdam, Bucharest, or Frankfurt, the focus remains consistent: finding analytical talent that can navigate the complexities of a global financial institution.

This visual timeline outlines the progression from your initial screening to final leadership rounds. Use this to pace your preparation; ensure you have refreshed your technical fundamentals before the mid-stage assessments and prepared your behavioral stories for the final manager-level discussions.

Technical Competency

You will be evaluated on your mastery of data extraction and manipulation. ING interviewers look for clean, efficient code and a deep understanding of database structures.

Be ready to go over:

• SQL Optimization: Understanding execution plans and indexing.
• Data Modeling: Designing schemas that support efficient reporting.
• Coding Standards: Writing maintainable and well-documented Python code.

Advanced concepts (less common):

• Cloud-based data warehouse architecture.
• Advanced statistical modeling for risk or fraud detection.

Example questions or scenarios:

• "How do you handle a join on two datasets with millions of rows?"
• "Explain how you would automate a manual reporting process."

Business Acumen and Domain Knowledge

It is essential to understand the context of the banking sector. You should be familiar with concepts like AML (Anti-Money Laundering) and KYC (Know Your Customer) if applying to fraud-related teams.

Be ready to go over:

• KPI Definition: How to define success metrics for banking products.
• Regulatory Awareness: The importance of data privacy and accuracy in finance.
• Stakeholder Management: Balancing competing priorities from different business units.

Example questions or scenarios:

• "How do you determine which features are most predictive of customer churn?"
• "How do you ensure your analysis complies with data protection regulations?"

As a Data Analyst at ING, you will act as a bridge between raw data and business intelligence. Your primary responsibility is to provide the analytical foundation for the Tribe or Chapter you support. This involves writing complex SQL queries to pull data, cleaning and transforming that data into a usable format, and building visualizations that highlight key trends.

You will often work in an agile environment, participating in daily stand-ups and sprint planning. Collaboration is constant; you will frequently translate business requirements into technical tasks for yourself or engineering teams. Whether you are optimizing a credit-scoring model or analyzing customer behavior in the mobile app, your work will be used to drive high-stakes decisions across the company.

A strong candidate for a Data Analyst role at ING typically possesses a blend of technical expertise and analytical curiosity. While requirements vary by seniority, the following are generally expected:

• Must-have skills: Advanced SQL proficiency is non-negotiable. You must also have strong skills in Python or R for data analysis and be familiar with visualization tools like Tableau, PowerBI, or Looker.
• Nice-to-have skills: Experience with cloud platforms (e.g., Azure, AWS, GCP), familiarity with Big Data tools, and knowledge of financial domain concepts like AML or risk management.
• Experience: A track record of delivering data-driven projects in a professional environment, with a clear ability to articulate the business impact of your work.

Q: How long should I prepare for the interview? A: Depending on your current familiarity with SQL and case studies, 2–3 weeks of focused practice is usually sufficient to brush up on technical skills and prepare your behavioral narratives.

Q: What is the most important thing to emphasize during the interview? A: Emphasize your ability to solve business problems using data. ING is not just looking for a coder; they are looking for an analyst who understands the "why" behind the numbers.

Q: Is the interview process mostly remote or in-person? A: Most interview processes at ING are conducted via video calls, though this can vary by location. Ensure your technical setup is ready for live-coding sessions.

Q: How can I stand out as a candidate? A: Show genuine interest in the banking sector and demonstrate that you can communicate effectively with non-technical stakeholders. Asking insightful questions about the team’s current data challenges will leave a strong impression.

• Structure your answers: Use the STAR method (Situation, Task, Action, Result) for all behavioral questions to keep your responses concise and impactful.
• Be ready for live coding: Practice writing SQL queries on a whiteboard or a simple text editor without the help of IDE autocomplete features.
• Show curiosity: Ask your interviewers about the data infrastructure at ING and how the analytics team handles technical debt.
• Understand the business: Read up on ING’s recent initiatives in digital banking and their commitment to sustainability.
• Be sincere: If you do not know the answer to a highly specific technical question, admit it, but explain how you would go about finding the answer.

The Data Analyst position at ING is a high-impact role that offers the opportunity to work at the forefront of financial technology. By focusing your preparation on SQL mastery, structured problem-solving, and clear communication of business insights, you position yourself as a top-tier candidate. Remember that the interviewers are looking for evidence of your ability to handle complex, real-world challenges with integrity and courage.

Use the resources on Dataford to refine your technical skills and practice your interview narratives. You have the potential to succeed; stay focused, be prepared, and approach your interviews with the confidence of an expert who understands the value they bring to the team.

The compensation data above provides a benchmark for this role. Use these figures to understand the market positioning for your level of experience and to guide your expectations during the offer negotiation phase.