Macquarie Group Data Engineer interview typically runs 3 rounds: online aptitude test, technical interview, and culture interview. The process completes in a few weeks and is distinguished by psychometric testing alongside technical depth.
$137K
Avg. Base Comp
$187K
Avg. Total Comp
4
Typical Rounds
2-4 weeks
Process Length
Our candidates report that Macquarie is looking for more than a capable SQL or Python user — they want someone who can explain the why behind every design choice. The strongest signal in the experience we saw was how consistently the conversation returned to real work: an ETL project walkthrough, a two-system migration scenario, and a table-based SQL problem that required reasoning through data integrity constraints rather than just writing a query. That pattern tells us Macquarie values practical engineering judgment over theoretical knowledge, and expects candidates to speak clearly about tradeoffs rather than recite patterns from memory.
A recurring theme is the emphasis on communication in a finance context. Multiple parts of the process probed stakeholder handling, current-role context, and motivation for joining Macquarie specifically — which suggests they care about whether you can operate credibly with non-technical partners as much as with engineers. We also noticed an explicit interest in AI usage in day-to-day work, which is a subtle but telling signal: they are not asking about hype, but about how you actually integrate new tools into a real workflow. Candidates who connect technical decisions to business impact and explain tooling choices with precision tend to land better here.
The other non-obvious pattern is breadth. Even for a Data Engineer role, the process included aptitude and psychometric components alongside a leadership and culture conversation, signaling that Macquarie is screening for structured thinking and professional maturity in parallel with technical depth. In our view, that combination means the bar is less about flashy system design and more about whether your experience feels grounded, consistent, and easy to trust.
Synthesized from 1 candidate report by our editorial team.
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Real interview reports from people who went through the Macquarie Group process.
The process felt fairly structured and moved quickly, but it was more demanding than I expected for a Data Engineer role. I went through two main interview rounds after an online aptitude test, and the overall flow was a mix of technical depth and behavioral fit. The first interview was about an hour and had around 8 or 9 questions. It started with introductions and a discussion of my current role, then moved into my ETL project, how I would handle migration when two systems are involved, and a SQL-style question about filtering out a customer using account, customer, and hold tables when an account can’t be deleted. They also asked about my AI skills, how I use AI in day-to-day work, stakeholder communication, and why I wanted to work at Macquarie. The questions were pretty role-specific, and I had to explain my past experience clearly rather than just give textbook answers.
The second stage was more of a technical design and deep dive on previous experience. That round focused on Python, SQL, data tools, and system design, with a case-study style discussion that went into the details of how I had handled work in the past. I also had a leadership or culture interview, which was more conversational but still touched on work experience and situational judgment. One thing I noticed is that the interviewers were nice and the atmosphere was positive, but they still expected solid technical grounding and clear communication. The aptitude and psychometric pieces made the process feel a bit broader than a standard technical screen. I didn’t get an offer in my case, but the process was professional and fairly well organized. If you’re preparing, I’d focus on being able to walk through an ETL project end to end, explain migration between systems, and talk concretely about your Python, SQL, and data tooling choices.
Prep tip from this candidate
Be ready to explain an ETL project end to end and to talk through a migration between two systems in detail. I’d also practice a SQL scenario involving multiple tables and deletion constraints, since that came up in a practical way.
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Topics based on recent interview experiences.
Featured question at Macquarie Group
Design a system to synchronize two continuously updated, schema-different hotel inventory databases at Agoda.
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Synthesized from candidate reports. Individual experiences may vary.
The process begins with an online aptitude and psychometric assessment used as an initial filter before live interviews. This broader evaluation goes beyond purely technical skills and is a distinguishing feature of Macquarie's hiring process.
The first live interview is a structured round with roughly 8-9 questions covering introductions, your current role, an ETL project deep dive, handling migration between two systems, a SQL problem involving account/customer/hold tables, AI usage in day-to-day work, stakeholder communication, and motivation for joining Macquarie.
The second round focuses on technical depth and past project execution using a case-study style format. Expect detailed discussion of Python, SQL, data tools, and system design, with interviewers probing how you made specific technical decisions in previous roles.
The final stage is a more conversational interview focused on leadership behaviors, situational judgment, and cultural fit. While the tone is positive and collegial, interviewers still expect clear communication and concrete examples from your work experience.
