Cloud Native Data Ops
Salla is hiring a Cloud Native Data Ops. Level rates it ; you can apply on Salla.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- Salla has 26 other open roles on Level.
AI in this role
We are looking for a Senior Site Reliability Engineer (SRE) to help design, scale, and secure our rapidly growing platform infrastructure.
You will work across all critical systems — from customer-facing applications and APIs to internal platforms and data services — ensuring availability, performance, and cost efficiency at scale.
You’ll be hands-on with Kubernetes, observability, GitOps, automation, and cloud infrastructure, while partnering closely with application, platform, and data teams to deliver a highly reliable and self-healing environment.
This role is ideal for an engineer who thrives on complex distributed systems, loves to automate everything, and can balance speed, stability, and cost-efficiency in production.
- Bachelor’s degree in Computer Science, Engineering, or a related field — or equivalent work experience.
- Design, deploy, monitor, and maintain production workloads across Kubernetes (EKS/AKS/GKE) clusters.
- Build self-healing, auto-scaling systems that minimize manual intervention and ensure uptime.
- Design and operate reliable database and storage platforms (SQL, NoSQL, and object stores) within Kubernetes environments.
- Implement backup, disaster recovery, replication, and failover strategies to meet RPO/RTO targets.
- Troubleshoot and recover Kubernetes Persistent Volumes (StorageClasses, CSI drivers, PVC issues).
- Optimize storage performance and cost through multi-tier strategies, hot/cold data separation, and S3/offloading lifecycle policies.
- Secure and scale object storage platforms (e.g., MinIO/S3-compatible) for high-throughput data pipelines.
- Manage block storage (EBS/io2/gp3) and shared file systems (EFS, NFS) for resilience and cost balance.
- Collaborate with teams to optimize networking, ingress/egress traffic, and service mesh for secure communication.
Platform & Infrastructure Reliability
- Design, deploy, monitor, and maintain production workloads across Kubernetes (EKS/AKS/GKE) clusters.
- Build self-healing, auto-scaling systems that minimize toil and manual intervention.
- Optimize networking, ingress/egress traffic control, and service mesh for secure & performant communication.
- Design and operate reliable database and storage platforms (SQL, NoSQL, and object stores) in Kubernetes environments.
- Own backup, disaster recovery, replication, and failover strategies to meet RPO/RTO targets for critical data services.
- Optimize storage performance and cost through multi-tier strategies, hot/cold data separation, and S3/offloading lifecycle policies.
- Troubleshoot and recover Kubernetes Persistent Volumes confidently during incidents (StorageClasses, CSI drivers, PVC issues).
- Secure and scale object storage platforms (e.g., MinIO/S3-compatible) and integrate with workloads for high-throughput data pipelines.
- Work with block storage (EBS/io2/gp3) and shared file systems (EFS, NFS) to balance performance, resiliency, and cost.
Automation & Delivery
- Champion GitOps and CI/CD best practices (ArgoCD, Flux, GitHub Actions).
Build automation for infrastructure provisioning and upgrades using Terraform, Helm, and Kubernetes Operators. - Reduce release risk through progressive delivery strategies (blue/green, canary, spot instance rolling updates).
Observability & Incident Response
- Own the monitoring and alerting stack (Prometheus, Grafana, Loki, VictoriaMetrics, OpenSearch).
- Lead incident management and postmortems to prevent recurrence.
- Provide real-time visibility into system health, performance, and cost metrics.
Security & Compliance
- Implement least-privilege IAM policies, secure service-to-service communication, and network ACLs/firewalls.
- Enforce Kubernetes RBAC, secret management, and secure image supply chain.
- Participate in audit readiness and compliance efforts.
Performance & Cost Optimization
- Analyze and tune system performance under scale (CPU/memory/IO).
- Partner with product and platform teams to right-size clusters, databases, and storage tiers.
Introduce cost visibility dashboards for engineering leadership.
Preferred Qualifications
- Experience managing mission-critical systems at scale (high traffic, multi-region).
- Proven cost optimization in cloud/K8s environments.
- Familiarity with service mesh (Istio, Linkerd) or advanced networking/egress control.
- Experience with data platform components (Airflow, Debezium, ClickHouse, etc.) is a plus but not required.
Strong communication skills and teamworker — able to collaborate across engineering, DevOps, security, and product teams.
Requirements
- 8+ years in SRE / DevOps / Infrastructure Engineering roles.
- Deep Kubernetes expertise (multi-cluster, Helm chart development, advanced networking).
- Strong GitOps workflows using ArgoCD/Flux.
- Expertise with AWS (preferred) or Azure/GCP, plus Infrastructure-as-Code (Terraform, Pulumi, CloudFormation).
- Advanced knowledge of SQL & NoSQL databases (MySQL/Aurora, PostgreSQL, MongoDB, Redis).
- Scripting/automation skills in Python, Bash, or Go.
- Solid background in monitoring/observability (Prometheus, Grafana, Loki, ELK/Opensearch, VictoriaMetrics).
- Experience with CI/CD at scale and managing production incidents.
- Experience with streaming/messaging (Kafka, RabbitMQ, or similar).
Benefits
- Comprehensive Training & Development programs.
- Performance-based Bonus incentives.
- Flexible Work From Home options.
How we rate this
Cloud Native Data Ops at Salla rates 32 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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