# Software Engineer 3, Data Pipeline

**Company**: MongoDB
**Location**: Dublin
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/mongodb/jobs/7613665?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_388625c0-b6f

## Description

The Data Pipeline team, within the MongoDB Observability organization, builds and supports scalable, highly available capabilities for transporting and transforming telemetry data across MongoDB.

We're looking for a Software Engineer 3 to help build and operate this platform. This is an individual contributor role that combines hands-on software development with systems and site reliability engineering.

Responsibilities:

- Design, write, test and maintain backend code and features for the Data Pipeline platform

- Contribute to and lead medium-sized technical projects through production delivery

- Help improve the scalability, availability, and reliability of telemetry ingestion, transformation, and delivery to downstream storage

- Investigate production issues using metrics, logs, and other evidence, and contribute to fixes and preventative improvements

- Participate in the team's on-call rotation and support customer escalations with support engineers and teammates

- Be customer-driven by collaborating with the sister teams and customers to improve the Observability user experience

- Contribute to technical discussions, code reviews, coding best practices, and operational improvements

Requirements:

- Enjoys working with other engineers, is approachable and curious, and is open to feedback

- Has experience with Kafka-compatible streaming platforms, Apache Flink, or comparable stream-processing technologies

- Has experience writing production backend systems in a compiled language, such as Java, Go, C, or C++

- Has experience designing and developing scalable distributed services, with an understanding of performance, availability, and failure handling

- Has worked with event-driven systems, ingestion pipelines, or high-throughput data processing

- Has hands-on experience managing the development and release lifecycle on Kubernetes clusters using GitOps tools such as Argo CD or Flux

- Has hands-on experience applying a data-driven approach to debugging and troubleshooting production systems using tools such as profilers and flame graphs to collect evidence

- Is comfortable being part of 24/7 on-call rotations

- Can explain their own technical contributions, the trade-offs they made, and the evidence used to evaluate results

- Has a strong understanding of algorithms, data structures, and time and space complexity

Nice to haves:

- Experience with telemetry, metrics, logs, or observability infrastructure

- Experience using service-level indicators, objectives, or agreements to guide reliability improvements

- Experience improving monitoring, alerting, incident response, or operational automation

Success measures:

- In 1 month, you'll be familiar with the systems the Data Pipeline team owns, the telemetry flow and the team's development practices, and you'll have completed minor codebase tasks

- In 3 months, you'll be contributing to the design and development of team projects and shipping changes regularly

- In 6 months, you'll be taking on small and medium-sized projects, contributing actively to technical discussions, proactively improving the platform, supporting customer escalations, and participating in the on-call rotation

## Skills

### Required
- Kafka-compatible streaming platforms
- Apache Flink
- Java
- Go
- C
- C++
- Kubernetes
- GitOps tools
- Argo CD
- Flux
- profilers
- flame graphs

### Nice to have
- telemetry
- metrics
- logs
- observability infrastructure
- service-level indicators
- objectives
- agreements

---

Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/mongodb/jobs/7613665?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)