Cloud Platform Engineer – Data Reliability, Backing Services

Responsibilities

• Own reliability, performance, scalability, and operational health of MySQL, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, Kafka, StarRocks, ClickHouse, and similar platforms
• Define best practices for how product engineering teams use transactional, document, search, messaging, and analytical platforms
• Design and maintain highly available, scalable, and resilient platform services, including replication, backup, recovery, failover, and disaster recovery capabilities
• Perform capacity planning, performance tuning, workload reviews, upgrades, patching, and lifecycle management for platform services
• Identify and resolve risks such as slow queries, hot partitions, consumer lag, replication lag, index growth, retention issues, and storage saturation
• Troubleshoot and resolve complex production issues related to databases, messaging systems, search platforms, and distributed data platforms
• Enable and support Kubernetes-based deployments of database, messaging, search, and analytical platforms using cloud‑native patterns and operational best practices
• Use automation, Infrastructure as Code, GitOps, and CI/CD to make backing services repeatable, reliable, and easier to operate
• Collaborate with Product Engineering, SRE, Security, Data Engineering, and Cloud Platform teams to improve reliability, performance, availability, and security posture

Requirements

• 4-7 years of experience in Platform Engineering, SRE, Database Reliability Engineering, Data Platform Engineering, DevOps, or related roles
• Strong hands‑on experience with MySQL, PostgreSQL, Kafka, and at least one of MongoDB or Elasticsearch/OpenSearch in production environments
• Experience with analytical or distributed data platforms such as StarRocks, ClickHouse, Apache Doris, Druid, Pinot, or similar OLAP systems is highly desirable
• Hands‑on experience operating stateful workloads in Kubernetes‑based environments
• Good understanding of high availability, replication, backup and recovery, disaster recovery, capacity planning, and performance tuning concepts
• Familiarity with distributed systems concepts including sharding, replication, partitioning, consistency, compaction, backpressure, consumer lag, and query optimization
• Experience with at least one major cloud platform (AWS, GCP, or OCI)
• Experience automating provisioning, deployment, configuration, monitoring, and lifecycle management using tools such as Terraform, Helm, Ansible, GitOps, or similar automation frameworks
• Strong scripting or programming skills in Python, Bash, Go, or similar
• Experience with observability platforms such as LTGM, Prometheus/Grafana, ELK/OpenSearch, Datadog, or equivalent
• Strong troubleshooting, problem‑solving, and debugging skills across distributed systems
• Excellent communication, collaboration, and documentation skills
• Demonstrated curiosity, ownership mindset, adaptability, and ability to guide product engineering teams

Core Competencies

Demonstrates expertise in managing and optimizing database platforms such as MySQL, PostgreSQL, and Kafka, with a strong focus on high availability, performance tuning, and disaster recovery. Proficient in automation and cloud‑native deployments, ensuring operational excellence across distributed systems.