Responsibilities
- Collaborate with Architecture, Product Engineering, and Security teams to design and enhance cloud-native data infrastructure.
- Develop automation and tooling for provisioning and scaling systems, emphasizing resilience, elasticity, and self-service capabilities using Crossplane.
- Integrate and manage new data storage technologies—including search, vector, in-memory, and caching systems—to meet platform-wide reliability standards.
- Engage with product and feature teams to understand their requirements and incorporate feedback into platform evolution.
- Design and implement disaster recovery strategies, including cross-region replication with defined recovery point and recovery time objectives.
- Monitor system health, performance, and observability using Datadog to proactively detect and prevent incidents.
- Lead incident response from detection through resolution within SLA, including post-mortem analysis, while sharing on-call duties across the team.
Team
Small, autonomous engineering team with end-to-end ownership of critical data systems used across the organization.
About the team
The Data Infrastructure team looks after the data backbone: how those events are taken in, processed, stored, and served, and everything that keeps them reliable, fast, and affordable to run. When a piece of data infrastructure becomes important enough that several teams depend on it, looking after it properly becomes our job. Today that estate covers Kafka (Amazon MSK), ClickHouse (on Amazon EKS), Amazon Aurora, and MongoDB (Atlas) across several AWS regions. We are now adding search, vector, and in-memory stores (OpenSearch, Redis, ElastiCache) to support new product work. You would join a small group of experienced engineers who own their areas from the first design through to running them in production. We like DevOps and CI/CD, we automate the things worth automating, and above all we care about doing the work well.
Why this role matters
Almost everything our customers rely on sits on top of this layer. When a product team promises customers high availability for what they have built, that promise only holds if the Kafka, the databases, and the streaming underneath hold too. Your work allows Nexthink to move quickly and trust the ground they are standing on.
How we work
A few things that are true about this team and, we think, make it a good place to build: - It is a small team with real ownership. You look after your own areas and make the call on what is best for the platform, rather than working through a queue of tickets someone else has written. - We do not work in a silo. We spend a lot of time with the teams who build on us, including a good deal of design work together, so the platform grows around what people genuinely need. - The scale keeps it interesting. We run across several regions on modern AWS tooling, which is a good deal more involved, and more rewarding, than a single-region setup. - We are improving something that already works. The platform is live and doing its job. Our task is to take it from good to really good, so the problems are about pushing things further rather than wiring up the basics. - Like everyone here we use AI tools day to day, and we are slowly moving the more repetitive operational work onto automation. We do it carefully, because infrastructure is not somewhere to be careless.
