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