Agoda - Senior/Staff Backend Engineer
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Requirements
• 6+ years of backend engineering and/or distributed systems experience (or equivalent impact). • Expert proficiency in modern C++ (C++17/20), especially for performance‑critical systems (concurrency, memory management, templates, profiling). • Strong foundations in algorithms, concurrency, networking, and Linux systems. • Hands-on experience with at least one MPP/OLAP system such as StarRocks, ClickHouse, Presto/Trino, Druid, Pinot, Doris, Impala, etc. • Practical expertise in query tuning and columnar analytics concepts (e.g., vectorized execution, statistics, cost-based optimization). • Proven experience operating distributed systems in production (monitoring, alerting, incident response, capacity planning). • Experience with containers and orchestration (Docker, Kubernetes) and Infrastructure as Code (Terraform/Helm/Ansible). • Strong communication skills and ability to partner effectively across platform, BI, and infrastructure teams. • Direct experience with StarRocks internals (FE/BE), materialized views, tablet management, and Lakehouse/Iceberg integration. • Contributions to open-source OLAP/DBMS projects (StarRocks or related ecosystems). • Experience building streaming ingestion (Kafka, Flink) and batch ingestion (Spark) into OLAP stores. • Knowledge of data governance, security, and compliance for analytics platforms. • Familiarity with cloud object storage and Lakehouse table formats (Iceberg, Delta, Hudi) and S3/GCS-compatible storage. • Deep performance tuning experience (profilers, SIMD/vectorization, CPU/memory optimization). • #Bangkok #Thailand
Responsibilities
• Design, implement, and operate StarRocks clusters to support high concurrency and sub‑second analytical queries at scale. • Plan and execute StarRocks upgrades and patch rollouts with minimal downtime (canary/blue‑green), including compatibility validation, regression testing, and rollback plans. • Develop features, extensions, and performance improvements to increase StarRocks stability and throughput; contribute upstream when broadly useful. • Build backend services and tooling around StarRocks for ingestion, connectors, governance, and observability. • Optimize query performance using materialized views, partitioning, statistics, and resource groups; make cost/performance trade‑offs. • Implement multi‑tenant controls, RBAC, auditing, and data protection to ensure governed access. • Automate operations (provisioning, autoscaling, backup/restore, upgrades) using Kubernetes and Infrastructure as Code. • Collaborate with Data Engineering, BI, and Product on data modeling and semantic layers. • Define and monitor SLOs, build dashboards, participate in on‑call rotations, and lead performance/reliability incident response.
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