MiQ DevOps Engineer Interview: Questions & Prep (2026)

MiQ is a global programmatic advertising and data science company with engineering offices across India. They currently have 6 open DevOps roles, making this a good window to apply. Their platform processes real-time ad bidding at scale, so the DevOps team works with infrastructure where reliability, speed, and cost efficiency all matter together.

Candidates report that the interview process typically runs 3-4 rounds. A recruiter call usually comes first, covering your background, notice period, and salary expectations. A technical round follows, focused on cloud platforms, containers, and scripting. Many candidates then face a system design or architecture discussion. A final conversation with a senior engineer or hiring manager typically closes the process. Some candidates also mention a short scripting or infrastructure-as-code task in between.

MiQ's engineering stack, based on publicly reported job descriptions, typically includes Kubernetes, Terraform, AWS or GCP, Helm, and CI/CD pipelines built on Jenkins or GitHub Actions. Observability tools and incident response practices come up frequently. Expect the conversation to be practical and scenario-driven rather than purely theoretical.

These questions are drawn from publicly reported MiQ interview experiences and common patterns for DevOps roles at programmatic advertising companies.

1. Walk us through a CI/CD pipeline you built or improved. What tools did you choose and why?
2. How have you managed Kubernetes clusters in production? Describe the hardest issue you debugged.
3. Describe your experience with infrastructure as code. How did you handle drift, state management, and team collaboration?
4. MiQ's platform processes real-time ad data at high volume. How have you designed or maintained infrastructure for low-latency, high-throughput workloads?
5. What does your observability setup look like? How do you decide what to alert on versus what to log?
6. Tell us about a production incident you were responsible for resolving. How did you find the root cause and prevent recurrence?
7. How do you manage secrets and enforce security best practices in a cloud environment?
8. What is your approach to auto-scaling? When do you choose horizontal scaling over vertical scaling?
9. How have you worked with software engineering teams to introduce DevOps practices earlier in the development cycle?
10. Describe a time you reduced cloud infrastructure costs without impacting reliability or performance.
11. How do you keep deployments consistent across dev, staging, and production environments?
12. What does a good on-call culture look like to you? How have you contributed to runbooks and post-mortems?

Q: Walk us through a CI/CD pipeline you built or improved.

*Situation:* My team was releasing a core microservice roughly once a fortnight because every deployment involved manual steps, environment-specific config files managed by hand, and no automated rollback path.

*Task:* I was tasked with automating the full release process, from code merge to production deployment, without disrupting the existing sprint schedule.

*Action:* I set up a GitHub Actions pipeline with stages for unit tests, Docker image builds, Trivy vulnerability scanning, and automated deployment to a Kubernetes staging cluster using Helm. I introduced environment-specific values files in version control and added a one-command rollback step using Helm rollback. I also added Slack notifications at each stage so the team had visibility without needing to check the pipeline manually.

*Result:* Releases became on-demand instead of fortnightly. The team shipped fixes the same day they were merged, and rollbacks that previously took hours were completed in minutes.

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Q: Tell us about a production incident you handled.

*Situation:* A traffic spike caused our ad-serving API to breach latency SLAs during peak hours. Dashboards showed rising error rates but the root cause was not immediately clear.

*Task:* I was on call and responsible for restoring service within our incident response window.

*Action:* I pulled metrics from Grafana and noticed a correlation between the spike and a misconfigured HPA (Horizontal Pod Autoscaler) that was not scaling fast enough. I manually scaled the deployment to handle immediate load, then identified that the HPA min-replicas value had been lowered in a recent config PR without proper review. I reverted the change, updated the review checklist to flag HPA settings, and wrote a post-mortem with a permanent fix.

*Result:* Service was restored within the incident window. The post-mortem was shared with the broader SRE team, and the updated checklist prevented similar misconfigurations in the following quarter.

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Q: Describe a time you reduced cloud infrastructure costs.

*Situation:* Our AWS bill had grown considerably over six months as the engineering team scaled up environments for new product features, but there was no formal process to clean up unused resources.

*Task:* I was asked to audit current spend and find savings opportunities without impacting development velocity.

*Action:* I used AWS Cost Explorer alongside resource tagging audits to identify idle EC2 instances, oversized RDS instances, and several S3 buckets with no lifecycle rules. I right-sized three RDS instances after load testing confirmed they were running well below capacity, set up lifecycle rules for old log archives, and introduced a nightly Lambda function that flagged untagged resources for review. I also moved non-critical workloads to spot instances.

*Result:* Cloud spend dropped meaningfully over the following two months, according to the team's internal tracking. The tagging and cleanup process was adopted as a quarterly ritual by the infrastructure team.

For 'tell me about a time' questions, use the STAR structure: Situation (one or two sentences setting context), Task (your specific responsibility), Action (steps you personally took, not 'we'), Result (an observable or measurable outcome). Keep the Situation brief. Interviewers lose interest if background takes more than 30 seconds.

For system design questions, start by clarifying requirements: expected traffic volume, SLAs, team size, and constraints. Then talk through your layers: compute, networking, storage, observability, and failure modes. MiQ deals with real-time data at scale, so show you have thought about latency budgets and what happens when a downstream service slows down or fails.

For tool-specific questions, do not just list tools. Explain why you chose them over alternatives and mention one real tradeoff you encountered. For example: 'We used Terraform over Pulumi because the team was already comfortable with HCL and the state management story was simpler for our multi-account AWS setup.'

For cost and reliability trade-off questions, show you understand the business context. In adtech, a few extra milliseconds of latency or a brief outage can mean lost bid opportunities. Frame your decisions in terms of that business impact, not just technical elegance.

MiQ interviewers, based on publicly reported candidate feedback, typically look for four things.

Ownership. They want engineers who treat infrastructure like a product, not a ticket queue. Show that you proactively identified problems, improved processes, and did not wait to be asked.

Cloud-native depth. Surface-level Kubernetes or Terraform knowledge will not get you far. Be ready to go into detail on cluster upgrades, state drift, or debugging failing pods under production load.

Cross-team collaboration. DevOps at MiQ sits at the intersection of platform, data, and product engineering. Candidates who show they can work with software teams to improve CI/CD practices and surface reliability concerns earlier in the cycle tend to stand out.

Operational maturity. How you respond to incidents, write runbooks, and contribute to post-mortems tells interviewers a lot about your on-call discipline and how you will handle pressure in a live environment.

Week 1: Refresh your core skills. Review Kubernetes architecture (pods, deployments, services, ingress, HPA, PVC). Practice writing Terraform modules for common AWS resources. Make sure you can explain your CI/CD setup in detail, including how you handled secrets, rollbacks, and environment promotion.

Week 2: Go deep on observability and incidents. Review or set up a Grafana/Prometheus stack. Write out two or three incident stories in STAR format. Be specific about the metrics you used, the timeline, and the changes you made after the incident.

Week 3: Practice system design out loud. Pick a scenario like 'design a deployment pipeline for a real-time bidding service' and talk through it as if you were in the room. Focus on failure modes, scaling decisions, and observability. Recording yourself helps you catch filler words and unclear explanations.

Before your interview: Look up MiQ's engineering blog and LinkedIn posts for recent infrastructure decisions. Map every tool in the job description to a real example from your experience. Prepare thoughtful questions to ask: what does the on-call rotation look like, how does the team handle post-mortems, and what is the biggest infrastructure challenge right now?

Saying 'we' instead of 'I'. Interviewers are evaluating your contribution, not your team's. When you describe past work, be specific about what you personally owned, decided, or built.

Memorising tool lists without depth. Listing Kubernetes, Terraform, and Jenkins on your resume invites hard follow-up questions. If you have touched a tool but do not know it well, be honest about your depth rather than implying expertise you do not have.

Skipping the 'why'. Explaining what you did is less convincing than explaining why you chose that approach over alternatives. MiQ interviewers want to understand your reasoning, not just your actions.

Neglecting the business context. Pure technical answers miss the mark. Tie your work to outcomes: faster releases, fewer incidents, lower costs, or a better developer experience.

Underestimating the final round. The conversation with a hiring manager is not a formality. Have honest answers ready for questions like 'how do you handle disagreement with a senior engineer?' and 'what kind of environment helps you do your best work?'

Not having questions ready. Candidates who ask nothing signal low interest. Prepare two or three specific, informed questions about the team, the stack, or the on-call culture.