The Data Pipeline team, within the MongoDB Observability organization, builds and supports scalable, highly available capabilities for transporting and transforming telemetry data across MongoDB. The team's mission is to provide a unified streaming pipeline that ingests data and processes high-throughput telemetry, enabling the migration of legacy observability solutions within MongoDB.
Built on a diskless, Kafka-compatible data streaming platform as the core streaming bus and Apache Flink for real-time transformations and delivery to storage, the platform lives on Kubernetes clusters and enables downstream consumers to access live telemetry for immediate analysis and reliable long-term retention. The main concern of this team is to provide reliable systems with high availability and replay capabilities.
About the roleWe'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. You'll contribute code and ship backend improvements, while also troubleshooting production issues and helping keep the services reliable.
If you enjoy both building distributed systems and understanding how they behave in production, this role offers the opportunity to work on high-volume telemetry processing with meaningful operational responsibility. You'll contribute to medium-sized technical projects and grow with support from experienced engineers.
We are looking to speak to candidates based in Dublin for our hybrid working model.
We're looking for someone who- 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
- 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
- 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
- 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
MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, relying on MongoDB for their most important applications, we’re powering the next era of software.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!
MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.
MongoDB is an equal opportunities employer.
Req ID: 1273361971
