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Redpanda Data

Cost-efficient Kafka-compatible streaming platform

Technical Support Engineer

Customer SupportConfirmed live in the last 24 hours
Full-timeNo salary listedRemote

About the Job

Requirements

  • Five or more years of experience in L3 support of enterprise products, with a significant focus on distributed systems.
  • Experience using AI tooling to automate repetitive tasks or enhance troubleshooting.
  • Strong understanding of Linux troubleshooting commands and regular expressions, including grep, awk, and sed.
  • Experience deploying and troubleshooting applications in Kubernetes.
  • Strong experience with public cloud providers and containerization.
  • Proficiency in Bash scripting and/or Python.
  • Willingness to participate in an on-call rotation.
  • Strong written communication skills.
  • Comfort working with a fully distributed engineering team and remote-first company.

Responsibilities

  • Serve as the primary customer-facing representative to ensure customer expectations are met or exceeded for Redpanda operations, including configuration, hardware, documentation, product, and feature requests.
  • Work with engineering to drive and resolve customer challenges from creation through resolution.
  • Partner with product engineering groups on periodic root cause analysis of customer issues and share lessons learned across the organization.
  • Build tools and services to improve support infrastructure, including issue life cycles and root cause trend analysis.
  • Participate in on-call rotations to provide follow-the-sun customer support.
  • Ensure customer satisfaction through strong relationships with the Customer Success team.

Desired Qualifications

  • Proficiency with Go.
  • Experience supporting a SaaS platform.
  • Experience supporting a streaming platform.

About the Company

Redpanda Data

Cost-efficient Kafka-compatible streaming platform

Redpanda offers a streaming data platform compatible with Kafka APIs, available as a fully managed cloud service or a self-hosted deployment. It ingests and stores real-time data and exposes it to applications through Kafka-compatible interfaces, aiming for high throughput and very low latency while reducing resource use. The platform differentiates itself by cutting infrastructure costs, simplifying deployment, and supporting both cloud and on-premises use, with Jepsen verification for safety and a focus on energy efficiency. Its goal is to provide a practical, easy-to-deploy, cost-effective way for organizations to process real-time data with minimal operational overhead.

Company size
201-500
Company stage
Series D
Total funding
$265.5M
Headquarters
San Francisco, CA
Founded
2019

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