Senior Data Ops & SRE Engineer (Remote/Hybrid)

Activision Blizzard

Santa Monica (CA)

Hybrid

USD 103,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Medical, dental, vision benefits

401(k) with company match

Relocation assistance

Job summary

Activision Blizzard is seeking a Senior Data Ops Engineer to strengthen reliability, observability, and data platform maturity across Kubernetes-based deployments and cloud environments. In this role, you will partner with data, analytics, and software teams to improve incident response, dashboards, and automation, while working on Databricks, Spark, Airflow, and related data tooling.

Flexibility includes a Los Angeles onsite option or remote work, with a hybrid schedule.

Qualifications

5+ years of experience in SRE, DevOps, cloud infrastructure, platform engineering, software engineering, data platform operations, or related production-support roles.
Hands-on experience supporting Kubernetes-based workloads, deployment systems, cloud infrastructure, or production application environments.
Familiarity with Linux, HTTP, DNS, containers, Kubernetes, Git-based workflows, and scripting in Bash, Python, or similar languages.
Experience with monitoring, logs, metrics, dashboards, alerting, and incident management practices.
Comfort working with event systems such as Kafka, Google Pub/Sub, Kinesis, or similar technologies, including topics, subscriptions, consumers, retries, lag, and dead-letter queues.
Strong troubleshooting mindset, clear communication, and comfort operating in a production-support environment.
Interest in data platforms, data engineering systems, orchestration, streaming workloads, event-driven architecture, internal developer tools, and production data services.

Responsibilities

Monitor service health, respond to alerts, and participate in incident response for cloud, Kubernetes, application, and data platform environments.
Investigate reliability issues across Kubernetes, networking, DNS, application runtime behavior, Databricks jobs, Spark workloads, orchestration systems, event systems, and dependent services.
Support the reliability of internal applications, APIs, workers, streaming consumers, event-driven services, and deployment workflows used by data engineering and business teams.
Build and maintain dashboards, alerting, runbooks, and operational documentation that improve detection and recovery speed.
Improve observability for Databricks environments, including job health, Spark streaming workloads, structured streaming metrics, cluster behavior, failures, latency, throughput, and cost signals.
Help route Spark streaming metrics, operational logs, event-system signals, and platform health signals into monitoring tools such as Grafana.
Contribute to alerting patterns for Databricks workflows, Airflow/Astronomer DAGs, dbt jobs, data freshness, pipeline failures, event lag, dead-letter queues, and production data dependencies.
Contribute scripts and automation that reduce repetitive operational work and improve environment hygiene.
Support release and deployment reliability by validating changes, improving rollback readiness, and strengthening change safety.
Partner with data engineers, analytics engineers, and software engineers to improve reliability across pipelines, services, internal tools, event systems, and data products.
Participate in post-incident follow-up and help close corrective actions that prevent recurrence.
Support platform modernization and migration efforts, including orchestration platform changes, deployment system improvements, and shared reliability standards.