Senior Site Reliability Engineer, Data Infrastructure

About the role

The Platform & Infrastructure Engineering team in the Data Infrastructure organization is responsible for the reliability, scalability, and security of the company’s data platform. The team builds and operates the foundational systems that power data ingestion, transformation, analytics, and internal AI workloads at scale. We operate with production-grade discipline, supporting mission-critical services with stringent uptime requirements and a focus on automation, observability, and resilience.

Responsibilities

• Own the reliability and performance of our Kubernetes-based data platform.
• Design and operate highly available, multi-region systems, ensuring our services meet strict uptime and latency targets.
• Work on scaling infrastructure, improving deployment pipelines, and hardening our security posture.
• Partner closely with engineering teams to ensure services are built for reliability from day one.
• Evolving our DevSecOps practices while playing a key role in system resilience, security, and operations.

Requirements

• 5+ years of experience in Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering roles.
• Deep expertise in Kubernetes and containerized software services, including cluster design, operations, and troubleshooting in production environments.
• Strong experience building and operating CI/CD systems, including tools such as Argo CD and GitHub Actions.
• Proven experience owning production systems with high availability requirements (≥99.99% uptime), including incident response, SLI/SLO/SLA definition, error budgets, and postmortems.
• Hands-on experience designing and operating geo-replicated, multi-region, active-active systems, including traffic routing, failover strategies, and data consistency tradeoffs.
• Strong experience building and owning observability components, including metrics, logging, and tracing (e.g., Prometheus, Grafana, OpenTelemetry).
• Experience with infrastructure as code (e.g., Helm, Terraform, Pulumi) and automated environment provisioning.
• Understanding of system performance tuning, capacity planning, and resource optimization in distributed systems.
• Experience implementing and operating security best practices in cloud-native environments (e.g., secrets management, network policies, vulnerability scanning).

Preferred Experience

• Operating data platforms or data-intensive workloads (e.g., Spark, Airflow, Kafka, Flink).
• Familiarity with service mesh technologies (e.g., Istio, Linkerd).
• Experience working in regulated environments with compliance frameworks such as GDPR, SOC 2, HIPAA, or SOX.
• Building internal developer platforms or self-service infrastructure.