Senior Site Reliability Engineer, Data & Analytics

Senior Site Reliability Engineer, Data & Analytics

At Blizzard Entertainment, our Site Reliability Engineers (SREs) use systems expertise combined with software engineering patterns to help define, create, and support the architecture, build systems, orchestration, and operations of services across the business. The role is composed of dedicated engineers focused on evangelizing reliability-as-a-feature through monitoring, service-level objectives, automation, everything-as-code, and testing.

This Senior SRE role is on our Data & Analytics team, which partners with data, analytics, and AI/ML teams across Blizzard to co-own the reliability of large-scale big data platforms, analytics pipelines, ML training pipelines, and inference services. Beyond traditional SRE work, this role is expected to help build the next generation of AI-based operational tooling, adopt agentic software development as a daily practice, and contribute to centralized AI services such as our internal MCP (Model Context Protocol) gateway that other engineering teams build on top of.

Blizzard's games and platforms reach a global audience of passionate gamers. The scale is massive, the data volume is enormous, and the challenges are very real, but wise application of technology — including AI — is the answer to keep it all running reliably with minimal toil. Our SREs are at the heart of this work, partnering directly with data, ML, and platform engineering teams from idea to launch to deliver the most epic (and reliable!) experiences ever.

This role offers a flexible hybrid work week, with a mix of remote and on-site days. While hybrid is the standard arrangement, you're also welcome to work on-site full-time if you prefer. Our primary studio location is Irvine, CA.

As an SRE at Blizzard, you may find yourself…

• Being part of an on-call rotation to assist finding a resolution during incidents
• Hosting blameless postmortems to share findings, discover gaps, embrace transparency, and improve reliability
• Building positive and collaborative relationships across data engineering, ML, and platform teams
• Employing your systems knowledge to triage problems and tune resource usage across batch and streaming workloads
• Championing automation to reduce toil and increase development velocity
• Helping define and instrument Service-Level Objectives to ensure epic player experiences
• Demonstrating Configuration Management to build and maintain consistency across services
• Building Terraform configs to manage infrastructure in GCP and other clouds
• Supporting and improving build pipelines with Jenkins, ArgoCD, and GitHub Actions
• Adopting Containers and Kubernetes for new and existing services
• Applying everything-as-code methodologies across configuration, infrastructure, orchestration, prompts, and agent definitions
• Designing, building, and operating AI-based operational tooling — agents, copilots, and runbook automations — that reduce on-call burden and accelerate diagnosis
• Using agentic software development workflows to deliver SRE work faster while maintaining code quality and ownership standards
• Building centralized AI tools such as our internal MCP gateway

You may succeed in this role if you…

• Love to solve novel and exciting problems, especially at the intersection of data systems and AI
• Dislike solving the same problems over-and-over — so you automate or eliminate them
• Are inspired to make everyone's job easier by improving workflows
• Are comfortable digging through metrics, logs, traces, lineage, and model telemetry to triage and fix an incident at any time
• Strive to be better, smarter, and faster tomorrow than you are today
• Enjoy trying new technologies — including rapidly evolving AI tooling — and can separate hype from durable value
• Naturally spread the philosophies and practices of DevOps and responsible AI use to others
• Like to collaborate with others to solve problems, share knowledge, and provide feedback
• Can self-assess the needs of a system or team, and make a case to prioritize that work
• Relish working with data, ML, software, network, cloud, and systems engineers to solve problems across all tiers of the stack
• Help your peers succeed as much as you can

Types of projects you may work on…

• Operating and improving Blizzard's massive global data platforms across multiple clouds
• Co-owning reliability of analytics pipelines (batch and streaming) and the data stores they feed
• Supporting ML training pipelines and inference services, including GPU-backed workloads
• Defining the future of running data and ML services on Kubernetes
• Building AI-based operational tooling: incident copilots, triage agents, automated runbooks, and self-service diagnostics
• Contributing to a centralized MCP gateway and the catalog of tools, data sources, and policies it exposes to other teams
• Integrating monitoring, logging, and lineage with systems to improve observability and enable Service-Level Objectives
• Performing and improving service migrations between clouds, regions, or platforms
• Designing and completing stress tests and load/cost modeling to validate scale expectations vs reality

Areas of Expertise for an SRE at Blizzard

SREs on this team are expected to become experts in the technologies used by the teams they support. Below is a non-exhaustive list of technologies you may be exposed to:

• Service-Level Objectives (SLI, SLO, SLA, Error Budget, Burn Rate), including data-quality and model-quality SLOs
• Distributed Systems (architectures, hybrid environments, high-availability)
• Big Data and Analytics (BigQuery, Dataflow, Dataproc, Airflow/Composer, dbt, Kafka)
• ML and Inference (training pipelines, feature stores, model registries, online/offline serving, GPU scheduling)
• AI Engineering (LLM application patterns, prompt and context engineering, evaluation, retrieval, agent frameworks)
• Model Context Protocol (MCP) servers and gateways, tool catalogs, and AI access control
• Container Computing (Docker, Kubernetes)
• GitOps (ArgoCD)
• Cloud Services and Architecture (GCP primary; AWS, OpenStack)
• Distributed Message Bus (Kafka, RabbitMQ, Pub/Sub)
• Proxies and Load Balancing (Nginx, HAProxy, ELB, ALB, GCLB)
• Monitoring (Prometheus, Grafana, Loki, Tempo, Kibana, Elasticsearch)
• Source Control (GitHub Enterprise)
• CI/CD (Jenkins, GitHub Actions)
• Linux (bash, debugging, performance tuning)
• Networking (triaging, packet loss, routing)
• Programming (Python, Go, Shell)

Minimum qualifications of a Senior SRE at Blizzard:

• Demonstrated production experience operating data, analytics, or ML/inference systems
• Hands-on experience using agentic software development workflows to ship real work, and clear judgment about where AI assistance helps vs. hurts
• Practical experience building or operating AI-powered tooling (e.g., LLM-backed automations, agents, MCP servers/clients) in a production or near-production setting
• Follows technology trends and industry standards passionately
• Capable of presenting ideas and technology to a broad audience in a clear and effective way
• Builds strong relationships with their partner teams and other SREs
• Eager to help others achieve their goals
• Co-owns operations and reliability with the partner team
• Demonstrates deep understanding of the services they support and their goals
• Explores new technologies with demos/experiments/labs
• Breaks down complex work into small units of work for themselves or others