Deloitte Cloud & Platform Engineer interviews, as candidates describe them, mix AWS, Kubernetes and Terraform technical questions with client-facing scenarios and an HR close. Rounds and format vary by team.
$137K
Avg. Base Comp
$171K
Avg. Total Comp
2-5 rounds
Typical Rounds
3 weeks
Process Length
Candidates describe a Deloitte cloud interview that mixes hands-on platform questions with consulting-style judgment, and the shape of the process differs from report to report. One candidate went through five rounds, another through a group discussion, a technical round and HR, and another through two technical rounds that were heavily scenario-based. Expect some variation by team.
On the technical side, Terraform and CI/CD depth comes up more than once. One candidate was asked to design Terraform modules from scratch and wire them into a multi-stage pipeline. Another was marked down only on Terraform module depth. AWS fundamentals also appear, including networking, multi-account security, NACLs versus security groups, and cost-based hosting choices. A Kubernetes report focused on control plane components alongside Linux and networking basics.
Scenario questions matter as much as service knowledge. Candidates report being asked to walk through modernizing a legacy application, migrating an on-prem SQL database with minimal downtime, and troubleshooting an SAP HANA system from the OS level. Interviewers seem to care about how you reason out loud, so rehearse structured answers rather than lists of services.
Behavioral and client-facing questions show up in managerial rounds: scope creep, a deployment failing during a client demo, and explaining cloud benefits to non-technical stakeholders. One candidate got guesstimate-style questions, and another faced a moderate pattern-printing exercise. Outcomes in the reports are mixed, with offers and rejections both represented.
Synthesized from 6 candidate reports by our editorial team.
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Featured question at Deloitte
Given two sorted lists, write a function to merge them into one sorted list.
| Question | |
|---|---|
| Maximum Profit | |
| Normalize Grades | |
| Real-Time Transaction Streaming | |
| Cyclic Detection | |
| Find Duplicate Numbers in a List | |
| Skyscanner Partner ETL | |
| Swap Variables | |
| Hurdles In Data Projects | |
| Portfolio Platform Architecture | |
| Data Pipelines and Aggregation | |
| User Event Data Pipeline | |
| Client Solution Pushback | |
| String Palindromes | |
| Open Source Reporting Pipeline | |
| Impossibly Iterative Fibonacci | |
| Text Editor With OOP | |
| Scalable Data Pipelines | |
| Simple Explanations | |
| Why Do You Want to Work With Us | |
| Your Strengths and Weaknesses | |
| Find the First Non-Repeating Character in a String | |
| Sort Strings | |
| Resumable Fact Table Load | |
| Real-Time Hashtag Partitioning | |
| Mouse Search | |
| Pipeline Transformation Failures | |
| Stakeholder Communication | |
| Marketing Workflow Optimization | |
| Azure Kubernetes Infrastructure |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial recruiter call or screen covering background, cloud projects, notice period, salary expectations and comfort moving between client engagements. One candidate instead described a group discussion that assessed communication and teamwork before any technical round. Treat it mainly as a fit check.
Candidates report a deep dive on a past cloud migration, then AWS topics such as networking, IAM, VPC and multi-account security. Others describe Kubernetes control plane components, Linux, networking, Terraform modules and CI/CD pipelines. A moderate pattern-printing programming question appeared in one report. Prepare to defend your project choices in detail.
One candidate reports a system design case for an AWS or Azure e-commerce platform at about one million daily users, covering scaling, caching, cost and HIPAA/GDPR. Others describe modernization, data migration and SAP HANA troubleshooting scenarios. Practice reasoning aloud step by step, since follow-ups can go deeper than the first answer.
Candidates report questions on scope creep, handling a failed deployment during a client demo, explaining cloud benefits to non-technical stakeholders and choosing the cheapest hosting option for a client. One candidate faced standard STAR prompts, and another faced guesstimate questions. A calm, structured approach to ambiguity appears to matter.
Candidates describe a final HR discussion of role, travel and review structure, a negotiation step, or in one case a partner-level conversation. One candidate noted salary was somewhat negotiable within published bands and that a background check began before the offer. Outcomes in the reports range from offers to no offer.
