The questions below are representative of what you will face. They are drawn from recent interview data and reflect our focus on observability, coding, and core infrastructure. Note that questions can vary significantly depending on the specific interviewer's background.

Technical: Observability & Tooling

This category tests your specific knowledge of the tools we rely on.

• "How do you perform deep-dive analysis using Splunk? Walk me through a complex query you have written."
• "What metrics would you track for a newly deployed microservice in Datadog?"
• "Explain the architecture of Splunk. How do indexers and forwarders work together?"
• "How do you handle log aggregation in a distributed microservices environment?"

Technical: Python & Scripting

Expect these to be practical but challenging.

• "Write a Python script that connects to an API, retrieves data, and filters it based on a specific key."
• "How would you use Python to automate the cleanup of old Docker images on a server?"
• "Explain the difference between a list and a tuple in Python. When would you use one over the other?"
• "Given a text file with server logs, write a script to find the top 5 most frequent IP addresses."

Infrastructure & General DevOps

These questions assess your foundational knowledge and problem-solving approach.

• "What are the best practices for securing a Docker container?"
• "Explain the concept of Microservices. What are the pros and cons compared to a monolith?"
• "How do you approach a situation where a deployment fails in production? Walk me through your rollback strategy."
• "Describe the difference between vertical and horizontal scaling in AWS."

• Python Fundamentals: Data structures (dictionaries, lists, sets), string manipulation, and file I/O.
• Automation Logic: Writing scripts to parse logs, automate API calls, or manage cloud resources.
• Algorithm Basics: You may occasionally see questions requiring basic algorithmic thinking, not just operational scripting.

Cloud Infrastructure & Containerization

We assess your practical experience with modern infrastructure.

• Containerization: Deep understanding of Docker (files, images, networking) and orchestration.
• AWS Services: Core services (EC2, S3, RDS, VPC) and how to secure them.
• Infrastructure as Code (IaC): While some interviews focus on theory, be prepared to discuss Terraform or CloudFormation best practices.

Example questions or scenarios:

• "Explain how you would use Splunk to troubleshoot a latency spike in a microservice."
• "Write a Python script to parse a log file and count the occurrence of specific error codes."
• "What is the difference between a Docker image and a container, and how do you optimize image size?"

Key Responsibilities

As a DevOps Engineer at S&P Global, your daily work revolves around ensuring the reliability and efficiency of our delivery pipelines. You will be responsible for designing, building, and maintaining the CI/CD pipelines that allow our development teams to deploy code safely and frequently. This often involves working with Jenkins, GitLab CI, or similar tools to automate testing and deployment gates.

Collaboration is a major part of the role. You will work alongside software developers to containerize applications using Docker and orchestrate them in cloud environments. You are expected to be the subject matter expert on infrastructure; when a developer has a question about why their service is failing in the staging environment, they will turn to you. You will also play a hands-on role in migrating legacy applications to microservices architectures, requiring a strong grasp of both the old and new worlds of tech.

Beyond deployment, you own the "health" of the system. This means you will spend significant time configuring and tuning observability platforms like Splunk and Datadog. You won't just look at dashboards; you will build them, creating the feedback loops necessary for teams to detect issues before our customers do. You will also write and maintain the Python scripts that glue these various systems together, automating manual operational tasks to reduce toil.

Role Requirements & Qualifications

We are looking for engineers who combine strong coding skills with operational discipline. The following breakdown helps you understand what is essential versus what is additive.

• Must-Have Skills:

  • Python: Proficiency is non-negotiable. You must be comfortable writing production-quality scripts and solving coding problems.
  • Observability Tools: Deep hands-on experience with Splunk (preferred) or Datadog. You need to know how to configure these, not just read them.
  • Containerization: Strong experience with Docker and container orchestration concepts.
  • Cloud Platforms: Solid understanding of AWS core services and networking.

• Experience Level:

  • Typically requires 3+ years of experience in DevOps, Site Reliability Engineering, or a hybrid Software Engineering/Operations role.
  • Experience working in regulated industries (Finance, Healthcare) is often a plus but not a strict requirement.

• Soft Skills:

  • Ability to explain complex technical concepts to non-technical stakeholders.
  • Patience and professionalism in navigating structured corporate environments.
  • Proactive problem-solving mindset—identifying risks before they become incidents.

Frequently Asked Questions

Q: How much coding should I expect? A: You should expect a significant amount. Unlike some DevOps roles that focus on YAML/Bash, S&P Global interviews frequently include a dedicated Python coding component. Treat this like a lightweight software engineering interview; review your data structures and standard libraries.

Q: Is the interview process consistent across all teams? A: There is some variability. While the core competencies (Cloud, Python, Observability) remain constant, the style of the interview can range from conversational architecture discussions to strict coding tests. Some candidates report warm, conversational panels, while others report more rigid technical interrogations.

Q: What is the work culture like regarding remote work? A: S&P Global generally operates on a hybrid model, though this depends on the specific office (e.g., Princeton, Toronto, Hyderabad). You should be prepared to discuss your ability to collaborate effectively in a distributed team environment.

Q: How deep do I need to go on AWS knowledge? A: It depends on the seniority of the role. For some rounds, high-level theoretical knowledge is sufficient. For others, specifically if you are interviewing for a senior post, you may be asked to detail how you secure pipelines or architect high-availability systems. It is safer to over-prepare on the details of core services (EC2, VPC, IAM).

Other General Tips

Master your Resume: Interviewers at S&P Global often use your resume as the primary script for the interview. If you list a tool like Kubernetes or a specific Python library, be prepared to answer deep-dive questions about it. Do not include technologies you cannot defend technically.

Prepare for "Misalignment": Some candidates have noted that interview questions felt different from the job description (e.g., a heavy coding focus for an Ops role). If this happens, stay calm and do your best. Acknowledge your strengths ("I primarily use Python for automation, but here is how I would approach this algorithm...") rather than resisting the question.

Check your Tech Setup: We conduct many interviews via video platforms. Ensure your camera and microphone are working perfectly. There have been instances where candidates were required to keep their cameras on even if the interviewer did not; maintain your professionalism and engagement regardless of the other party's setup.