Senior Cloud Engineer

About Company

At Delaplex, we believe true organizational distinction comes from exceptional products and services. Founded in 2008 by a team of like-minded business enthusiasts, we have grown into a trusted name in technology consulting and supply chain solutions. Our reputation is built on trust, innovation, and the dedication of our people who go the extra mile for our clients. Guided by our core values, we don't just deliver solutions, we create meaningful impact.

• 7–12 years of overall engineering experience, including significant hands-on work in Cloud Engineering, Platform Engineering, SRE, Data Infrastructure, or distributed backend systems.
• Strong hands-on experience with Google Cloud Platform (GCP), including GKE, Compute Engine, Google Cloud Storage, Artifact Registry, IAM, VPC, load balancing, Cloud NAT, Cloud Logging, Cloud Monitoring, Secret Manager, and Cloud Audit Logs.
• Strong production experience with Kubernetes and Docker, including workloads, networking, ingress, storage, secrets, RBAC, autoscaling, health checks, resource management, node pools, and upgrades.
• Demonstrated experience deploying and operating distributed, data-intensive, or stateful systems on Kubernetes or cloud infrastructure.
• Hands-on experience with Apache Doris or a comparable distributed analytical database such as ClickHouse, Apache Druid, StarRocks, BigQuery, Snowflake, or Redshift; Apache Doris experience is strongly preferred.
• Hands-on experience with Apache Iceberg or comparable open table formats and data lake technologies; understanding of catalogs, metadata, partitioning, schema evolution, compaction, and lifecycle management.
• Strong experience with Google Cloud Storage or comparable object storage, including data organization, lifecycle rules, access control, performance considerations, and cost management.
• Experience deploying or managing Dask, Ray, Spark, or a comparable distributed compute framework; experience running Dask on GKE is preferred.
• Good understanding of modern data-pipeline architectures spanning ingestion, transformation, orchestration, analytical storage, object storage, serving layers, and downstream consumers.
• Experience with workflow orchestration platforms such as Prefect, Apache Airflow, Dagster, Argo Workflows, or equivalent technologies.
• Strong understanding of distributed-systems fundamentals, including partitioning, replication, consistency, fault tolerance, backpressure, retries, idempotency, and failure recovery.
• Ability to size and tune systems using workload metrics such as data volume, throughput, concurrency, latency, CPU, memory, GPU utilization, storage I/O, and network transfer.
• Experience designing highly available architectures and operating stateful services with persistent storage on Kubernetes.
• Hands-on experience with Terraform or an equivalent Infrastructure as Code tool.
• Strong scripting and automation skills using Python, Bash, PowerShell, or similar languages.
• Experience with Azure DevOps or comparable CI/CD platforms, including YAML pipelines, environments, service connections, approvals, secrets, and deployment automation.
• Experience implementing observability for cloud and data platforms using metrics, centralized logging, alerting, dashboards, and distributed tracing.
• Ability to diagnose production issues across applications, data jobs, Kubernetes, compute, storage, networking, permissions, and cloud services.
• Strong understanding of cloud networking, including VPCs, subnets, DNS, NAT, load balancers, private connectivity, TLS, firewall rules, and network security.
• Strong understanding of IAM, RBAC, least privilege, service accounts, privileged access, access reviews, secrets management, and segregation of duties.
• Experience with backup, restore, disaster recovery, RTO/RPO, high availability, failover, redundancy, and business continuity practices.
• Experience managing upgrades, patching, vulnerability remediation, and secure software delivery for cloud and containerized platforms.
• Working knowledge of security and observability tools such as Google Security Command Center, Microsoft Defender for Cloud, Wazuh, Trivy, SonarQube, Open Telemetry, Prometheus, Grafana, or equivalent platforms.
• Ability to evaluate build-versus-managed-service trade-offs across reliability, operational complexity, performance, scalability, and cost.
• Ability to produce clear architecture documentation, runbooks, capacity plans, operational procedures, and audit evidence.
• Strong ownership mindset and the ability to independently investigate, stabilize, and improve complex production Platforms.
• Experience in SaaS, retail, supply chain, analytics, optimization, or AI platforms and in startup or fast-moving product teams - is preferred.
  
  

Skills: kubernetes,platforms,google,data,apache,google cloud,management,storage,cloud