Data Platform Engineer

Why LINE MAN Wongnai LINE MAN Wongnai is one of Thailand's fastest-growing technology companies, operating three core business groups: On-demand Services under the LINE MAN brand, the leader in food delivery, mart delivery, messenger, transportation, and telepharmacy; Merchant Digital Solutions under the Wongnai brand, the leading provider of POS and digital solutions for merchant management, beauty, and wellness clinics; and Pay & Financial Services under the LINE Pay brand, an integrated online and offline payment platform. As a data and AI-driven company, our mission is to Digitalize Everyday Life Services, guided by our core values: Innovate Faster, Go Deeper, and Respect Everyone. Together, we power a digital ecosystem that serves 10 million users, 520,000 active online and offline merchants, and over 290,000 active riders and drivers nationwide. Join us, and you'll work alongside talented, driven people who take real ownership from day one. Here, your work won't just move a project forward, it'll shape how millions of people live every day. As a Data Platform Engineer, you will build, operate, and troubleshoot our data infrastructure end to end — from bare VMs and Kubernetes clusters to self-service platform tooling. You will be on the front line of keeping our data stack stable and fixing runtime issues when they happen. Deploying a service and keeping it stable is the baseline of this role. Deciding what a service should and should not do is the next step, and it is where you grow into the senior level. What you will do: Infrastructure & Platform Operations: Deploy and operate platform services on Kubernetes using Helm, ArgoCD, and GitOps practices.Infrastructure as Code: Manage and provision our infrastructure with Terraform.Performance & Scale: Tune what we run, so it keeps up as the platform grows. The bigger our platform gets, the more tuning it needs.Self-Service Tooling & Automation: Build in-house tools that turn manual platform work into self-service platforms.Troubleshooting & Observability: Set up monitoring, dashboards, and alerts with Prometheus and Grafana. Debug how our systems behave under load, and write the runbooks.Incident Response: Handle production incidents, find the real root cause, and take part in post-mortems.Collaboration: Work with data engineers, data scientists, business intelligence analysts, and software engineers to unblock them and make the platform easier to use. What you will need: Education: Bachelor's degree or equivalent experience in Computer Science, Information Technology, Engineering, or related fields.Programming: Strong programming skills (Python and/or Java preferred).Systems & Kubernetes: Strong Linux and networking basics. Able to deploy and manage an application on Kubernetes with Helm and ArgoCD / GitOps practices.DevOps & CI/CD: Experience with DevOps practices, and able to build and maintain a CI/CD pipeline.Observability: Able to set up monitoring and alerts with Prometheus and Grafana.IaC: Experience managing infrastructure with Infrastructure as Code.Analytical Mindset: You can explain your troubleshooting steps and justify your technical choices, not just show us the fix.Language & Location: Proficient in English and Thai, and based in or close to Thailand, or willing to relocate. It'd be Great if you have: Hands-on experience with a data stack like ours — Apache Airflow, lakehouse architectures, the Hadoop ecosystem, Databricks, or a data warehouse. You don't need to be a deep expert, but if you have worked on this kind of stack before, you will find your way around much faster.Understanding of how a platform component behaves at large scale — for example, what to tune when Airflow runs thousands of DAGs.Understanding of how Spark or Flink runs a job, and how you would process 100 GB+ of data efficiently.Experience with an OLAP data warehouse, e.g. ClickHouse, Doris, StarRocks, Redshift, or SQL Server.Experience building an in-house service yourself, front-end and backend.Experience with Apache Iceberg or another open table format.Experience with managing infrastructure for BI Tools (e.g. Tableau, PowerBI, Redash, Metabase, Superset, etc.)