EY Global Delivery Services ( EY GDS) Data Engineer interview questions & guide 2026

The questions below are representative of the patterns observed in recent candidate experiences. While specific technical hurdles depend on your interviewer's focus, you should expect a blend of rigorous coding assessments and deep-dive architectural discussions.

SQL and Data Manipulation

These questions test your ability to handle complex data retrieval and transformation tasks, which are fundamental to the role.

• Find the second highest salary in each department.
• Explain the use of window functions in SQL.

Success at EY Global Delivery Services ( EY GDS) requires more than just technical proficiency; it requires the ability to articulate why you chose a specific tool or method. Prepare to narrate your technical decisions as clearly as you write your code.

Role-related knowledge – You must have a firm grasp of SQL, Python, and PySpark. Interviewers look for deep technical fluency rather than surface-level familiarity; be prepared to discuss the "how" and "why" behind your technical choices in previous projects.

Problem-solving ability – You will be presented with scenario-based challenges. Focus on structuring your response by first clarifying requirements, then proposing a scalable solution, and finally addressing potential trade-offs regarding performance or cost.

Communication and Clarity – Since this role involves cross-functional collaboration, the ability to explain complex technical concepts to non-technical stakeholders is vital. Practice articulating your project history, including the specific challenges you faced and the impact of your solutions.

The interview process at EY Global Delivery Services ( EY GDS) is designed to be efficient yet thorough. Most candidates experience a streamlined progression, often moving from an initial technical screening to detailed one-on-one deep dives. The firm prioritizes candidates who demonstrate both strong analytical skills and a clear understanding of the business value behind data engineering.

Expect the process to be highly project-centric. Rather than relying solely on abstract algorithm questions, interviewers will likely challenge you to apply your knowledge to the specific data problems you have solved in your career. The overall atmosphere is professional, and you should be ready to discuss your technical work with precision.

This visual timeline illustrates the typical flow from initial screening to final technical and behavioral rounds. Use this to pace your preparation, ensuring you have refreshed your project details before the technical deep-dive stages. Note that for some candidates, the process can move very quickly—often in under two weeks—so maintain a state of readiness throughout.

Project-Based Technical Deep Dive

Your past projects are the centerpiece of your interview. You are expected to demonstrate ownership, technical depth, and an understanding of project lifecycle management.

Be ready to go over:

• Architecture design – Explain the rationale behind your tech stack choices.
• Root cause analysis – Describe how you handled data remediation and debugging.

As a Data Engineer, your primary responsibility is the end-to-end management of data pipelines. This involves everything from data ingestion and transformation to storage and delivery. You will spend a significant portion of your time writing efficient SQL and Python code to ensure that data is not only accessible but also reliable and accurate.

Collaboration is a daily requirement. You will work closely with other technical teams to integrate data solutions into broader business platforms. Whether it is debugging a pipeline, optimizing a query, or implementing a new cloud feature, your work ensures that the organization can leverage its data as a strategic asset. You will also be expected to maintain documentation and adhere to internal data governance standards.

A competitive candidate for the Data Engineer position at EY Global Delivery Services ( EY GDS) combines strong technical fundamentals with a proven track record of project delivery.

• Must-have skills:
  • Advanced proficiency in SQL (including window functions, CTEs, and complex joins).
  • Strong programming skills in Python.
  • Hands-on experience with PySpark and big data processing.
  • Cloud platform experience (e.g., AWS or Azure).
• Nice-to-have skills:
  • Experience with Databricks or Azure Data Factory (ADF).
  • Knowledge of data modeling patterns like Star and Snowflake schemas.
  • Exposure to data governance and lineage tools.

Q: How much time should I spend preparing for the interview? A: Given the fast-paced nature of the hiring process, you should aim to be "interview ready" as soon as you apply. Focus your preparation on the projects listed in your resume and brush up on core SQL and Python concepts.

Q: Is the coding test difficult? A: The technical tests generally range from easy to medium in difficulty. The focus is on your ability to write clean, working code to solve common data manipulation tasks rather than solving highly obscure algorithmic puzzles.

Q: What is the most important thing to focus on for success? A: Clarity in communication. Being able to explain your technical decisions and the "why" behind your architecture is what separates successful candidates from the rest.

Q: Does the interview process vary by location? A: While the core technical requirements remain consistent, the specific panel members and their focus areas can vary. Be prepared for the interview to be tailored to the specific team's needs.

• Own your resume: Every line on your resume is fair game. If you mention a technology, be prepared to answer deep-dive questions about your practical application of it.
• Practice SQL consistently: SQL is a recurring theme across almost all interviews for this role. Ensure you can write queries comfortably without hesitation.
• Focus on the "Why": Don't just explain what you did; explain why you chose that specific approach over alternatives. This demonstrates seniority and technical maturity.
• Prepare for behavioral questions: Don't ignore the HR round. Be ready to discuss your long-term career goals and why you are interested in the firm.

The Data Engineer role at EY Global Delivery Services ( EY GDS) offers a unique opportunity to work on high-impact, global data initiatives. By focusing your preparation on mastering SQL, Python, and your own project history, you will be well-positioned to succeed. Remember that your ability to articulate your technical contributions is just as important as the code you write.

You can explore additional interview insights, practice questions, and preparation resources on Dataford. With a structured approach and clear focus, you can confidently navigate the interview process and demonstrate the value you bring to the team.

This module provides a window into typical compensation structures for this role. Use this information to understand the total reward package, which often includes a base salary and potential performance-based components, and ensure you have a clear understanding of your expectations before entering final discussions.