Devops Engineer

Get to Know the TeamThe Coban team, part of the Data Tech Family, is the superstar data streaming team at Grab. We are architecting and operating large-scale, mission-critical data streaming platforms that serve engineers from all of Grab's verticals, processing low latency, multi-TB/hour workloads with 99.99% uptime.Our multicultural team is made up of brilliant and passionate Infrastructure Engineers and Data Engineers. If you are looking for an opportunity that allows you to design and manage a large-scale data infrastructure in a highly stimulating environment, look no further!Get to Know the RoleWe are looking for a Devops Engineer who would be thrilled at architecting and operating one of the biggest data platforms in Southeast Asia, with a passion for automation and a strong sense of customer service. An engineer in this role would build on inflight data that is of terabyte-scale and distributed systems that routinely serve tens of thousands of queries every second with tight SLAs.In this role, you would get the opportunity to be part of a team that designs and operates the mission-critical infrastructure that processes every piece of data generated or consumed by Grab's systems.The role will be based in either Hanoi or HCMC officeThe Day-to-Day Activities:Designing, deploying, and operating large-scale data streaming infrastructure in the public cloud (AWS). Consistently finding opportunities to improve and optimize the workloads for reliability, performance, and cost.Creating intelligent GitOps solutions and Gitlab CI pipelines for next-level cloud infrastructure and resource provisioning (Kafka topics, streaming pipelines).Investigating, mitigating, and resolving incidents such as production outages performance degradation, or data loss, in particular around Kafka and Kubernetes. Authoring post-mortems, identifying and implementing longer-run corrective actions. Taking turns in providing on-call support for Coban in autonomy.Running upgrades (EKS, Operating System…) as well as routine maintenance operations at night. Identifying opportunities to reduce the toil by building automation.Finding opportunities to collaborate with our main stakeholders such as the Cloud Infrastructure, Cybersecurity, and Compliance teams, as well as the other data teams of Data Tech (data lake, machine learning, segmentation…). Ensuring that their requirements are built into automated guardrails in our platforms and products.Supporting our users in their needs of more real-time data, always with a view to self-service and automation where possible.Experimenting and rolling out new cross-cutting technologies - container clusters and service mesh, Kubernetes operators, modern stream processing platforms, secrets management, monitoring and logging solutions, and more.