At Fivetran, data integration is the core product. The DevOps Engineer—frequently designated internally as a Site Reliability Engineer (SRE)—is the backbone of the infrastructure that powers thousands of automated ELT (Extract, Load, Transform) pipelines. The platform moves terabytes of critical business data across multiple cloud environments every single day, requiring an infrastructure that is secure, scalable, and resilient.

As a DevOps Engineer or Site Reliability Engineer at Fivetran, you will work on solving the complex engineering challenges that come with multi-cloud deployments. Your work directly impacts the stability and performance of the data pipelines that Fivetran's customers rely on for real-time business intelligence. This means you will be building and maintaining containerized environments on Kubernetes, automating cloud infrastructure provisioning, and designing self-healing systems capable of handling massive spikes in data throughput.

This is a highly collaborative and strategic role. You are not just managing infrastructure; you are partnering with product engineering teams to ensure that new services are architected for high availability and low latency. If you enjoy solving deep systems-level problems, optimizing cloud spend, and building robust automation that eliminates manual toil, this role offers an exceptionally high-impact environment.

The following questions are representative of what you can expect during the Fivetran evaluation process. These questions are drawn from real interview experiences and are designed to test both your fundamental systems knowledge and your practical problem-solving capabilities under pressure.

Kubernetes & Container Orchestration

This category evaluates your deep understanding of container networking, cluster state management, and troubleshooting in containerized environments.

• Explain the fundamental difference between a ClusterIP and a NodePort in Kubernetes.
• What is a Kubernetes Service at its core, and how does it route traffic to pods?

To succeed in the Fivetran technical loop, you must demonstrate a balance of strong systems fundamentals, practical coding skills, and a collaborative mindset. Your preparation should focus on the following core evaluation criteria:

Role-Related Knowledge – You must possess a deep, working knowledge of cloud platforms (specifically AWS and GCP), infrastructure-as-code (Terraform), and container orchestration (Kubernetes). You should be prepared to explain not just how to use these tools, but the underlying mechanisms of how they function.

Problem-Solving & Troubleshooting – Interviewers want to see how you approach ambiguity. When faced with a broken system or a complex architectural problem, you should demonstrate a structured, logical methodology. Avoid jumping to conclusions; instead, isolate variables, ask clarifying questions, and state your assumptions clearly.

System Design & Scalability – You need to show that you can design systems that are resilient, scalable, and cost-effective. Be ready to discuss the trade-offs of your architectural choices, particularly regarding data consistency, network latency, and operational complexity in a multi-cloud environment.

Collaboration & Cultural Alignment – At Fivetran, SREs and DevOps Engineers work closely with product developers and leadership. You must demonstrate strong communication skills, empathy for developers, and the ability to explain complex infrastructure concepts to non-technical stakeholders.

The interview loop for a DevOps Engineer or Site Reliability Engineer at Fivetran is exceptionally rigorous and comprehensive. The process is designed to thoroughly evaluate your technical depth, coding proficiency, system design capabilities, and cultural fit. You will interface with a diverse group of engineers, team leads, and directors throughout the cycle.

You can expect a multi-stage process that typically spans several weeks. The initial rounds focus on aligning your experience with the team's needs and evaluating your fundamental knowledge. As you progress, the interviews shift toward highly practical, hands-on simulations, including live coding and real-time system troubleshooting. The final stages focus on high-level system design, leadership alignment, and cultural integration.

The visual timeline above outlines the typical progression of the Fivetran hiring loop, starting from the initial recruiter outreach through to the final leadership sync. Candidates should use this timeline to pace their preparation, ensuring they allocate ample time to practice coding and troubleshooting before entering the mid-stage technical simulations. Because the process involves multiple specialized rounds, maintaining technical consistency and clear communication across all stages is critical.

Kubernetes & Infrastructure-as-Code

This evaluation area focuses on your ability to deploy, manage, and scale applications in cloud environments safely and efficiently. You must show a deep familiarity with Kubernetes primitives and declarative infrastructure management.

Be ready to go over:

• Kubernetes Networking – How pods communicate, service discovery, and the mechanics of Kube-Proxy.
• Terraform State Management – Managing state in multi-developer teams, locking, and structuring modular code.
• Cluster Autoscaling – Configuring node pools, pod disruption budgets, and resource quotas to optimize cost and performance.
• Advanced concepts (less common) – Service meshes (such as Istio or Linkerd), custom resource definitions (CRDs), and writing custom Kubernetes operators.

Example scenarios:

• "Explain how you would migrate a legacy application running on virtual machines into a Kubernetes cluster with zero downtime."
• "How would you structure your Terraform code to manage identical environments across development, staging, and production while minimizing code duplication?"

Scripting & Live Troubleshooting Simulation

This is a highly practical round where you will be expected to write code and debug systems in real time. Fivetran values engineers who can write clean, production-grade scripts to automate operations and quickly diagnose system failures.

Be ready to go over:

• Log Parsing & Data Manipulation – Using Python or Go to process large text files, extract key metrics, and format data.
• API Integration – Writing scripts that interact with cloud provider APIs or monitoring tools to automate administrative tasks.
• Linux Systems Internals – Understanding CPU, memory, disk I/O, and network troubleshooting commands (e.g., strace, lsof, tcpdump, htop).

Example scenarios:

• "You are given access to a terminal where a web service is returning 502 Bad Gateway errors. Walk us through how you would locate the failure and fix it."
• "Write a script that queries the AWS API to find all EC2 instances without specific compliance tags and sends a slack notification with the list."

System Design & Multi-Cloud Architecture

In this round, you will design infrastructure to support high-throughput, distributed applications. You must demonstrate that you understand how to build systems that scale horizontally and handle failures gracefully.

Be ready to go over:

• High Availability & Disaster Recovery – Multi-region replication, failover strategies, and backup verification.
• Observability Stack Design – Implementing structured logging, metrics collection (Prometheus/Grafana), and distributed tracing.
• CI/CD at Scale – Designing deployment pipelines that incorporate automated testing, canary deployments, and automated rollbacks.
• Advanced concepts (less common) – Multi-cloud networking architectures, hybrid-cloud connectivity, and zero-trust security models.

Example scenarios:

• "Design a continuous delivery pipeline that safely deploys updates to a critical service running across hundreds of Kubernetes clusters globally."
• "How would you design a centralized logging infrastructure that can ingest, index, and retain terabytes of log data daily while keeping storage costs low?"