Job Title:Senior Data Ops Engineer, Data Activation & Products - Activision
Requisition ID:R028025
Job Description:Your MissionWe are looking for a Site Reliability Engineer to help improve the reliability, observability, and operational maturity of our data platforms, Kubernetes-based deployment systems, internal applications, and cloud environments.
This role sits at the intersection of SRE, DevOps, and data. The ideal candidate is comfortable operating production systems, troubleshooting across infrastructure and applications, and helping teams deploy and support services more safely.
The role does not require someone to be a data engineer, but they should be excited about the systems that support modern data engineering, including Databricks, Spark, Airflow/Astronomer, streaming pipelines, event systems, internal tools, and backend services.
We are especially interested in a creative, curious engineer who enjoys learning new technology and using AI-accelerated development practices to solve problems faster and more thoughtfully. You should be excited to experiment with agentic development tools, automation frameworks, and emerging platform capabilities, while applying sound engineering judgment.
This role has the option to be based in our Los Angeles (Pen Factory) office and follows an onsite work schedule of Monday through Thursday or be remote. Work arrangements may change at the company's discretion to meet business needs.
Priorities can often change in a fast-paced environment like ours, so this role includes, but is not limited to, the following 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.
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.
Nice to Have- Experience with Kubernetes deployment and release tooling such as Helm, ArgoCD, or similar GitOps workflows.
- Experience with CI/CD automation using GitHub Actions, GitLab CI, Jenkins, or similar pipelines.
- Familiarity with infrastructure as code using Terraform or similar provisioning tools.
- Familiarity with Databricks, Spark, Spark Structured Streaming, Airflow, Astronomer, dbt, Kafka, Pub/Sub, object storage, or lakehouse architectures.
- Experience with observability tools such as Grafana, Prometheus, Cloud Monitoring, Datadog, Splunk, or similar platforms.
- Experience supporting internal applications, APIs, event-driven services, streaming consumers, or backend workers.
- Exposure to data reliability concepts such as freshness, latency, completeness, pipeline health, data quality checks, and dependency-aware alerting.
- Exposure to SLOs, SLAs, error budgets, postmortems, or formal reliability practices.
What Success Looks Like- Kubernetes and deployment workflows are easier to operate, monitor, and troubleshoot.
- Databricks, Spark, streaming, orchestration, event-driven, and dbt environments have clearer dashboards, alerts, and runbooks.
- Spark streaming metrics, event-system health signals, and platform logs are easier to access, visualize, and operationalize through tools such as Grafana.
- Incidents are detected faster, resolved more efficiently, and followed up with meaningful corrective actions.
- Data engineers, analytics engineers, and software engineers can deploy changes more safely and with greater confidence.
- Repetitive operational work is reduced through automation and better platform standards.
- Platform migrations and modernization efforts are supported with strong reliability, observability, and operational practices.
RewardsWe provide a suite of benefits that promote physical, emotional and financial well-being for 'Every World' - we've got our employees covered! Subject to eligibility requirements, the Company offers comprehensive benefits including:
- Medical, dental, vision, health savings account or health reimbursement account, healthcare spending accounts, dependent care spending accounts, life and AD&D insurance, disability insurance;
- 401(k) with Company match, tuition reimbursement, charitable donation matching;
- Paid holidays and vacation, paid sick time, floating holidays, compassion and bereavement leaves, parental leave;
- Mental health & wellbeing programs, fitness programs, free and discounted games, and a variety of other voluntary benefit programs like supplemental life & disability, legal service, ID protection, rental insurance, and others;
- If the Company requires that you move geographic locations for the job, then you may also be eligible for relocation assistance.
Eligibility to participate in these benefits may vary for part time and temporary full-time employees and interns with the Company. You can learn more by visiting https://www.benefitsforeveryworld.com/.
In the U.S., the standard base pay range for this role is $102,800.00 - $190,204.00 Annual. These values reflect the expected base pay range of new hires across all U.S. locations. Ultimately, your specific range and offer will be based on several factors, including relevant experience, performance, and work location. Your Talent Professional can share this role's range details for your local geography during the hiring process. In addition to a competitive base pay, employees in this role may be eligible for incentive compensation. Incentive compensation is not guaranteed. While we strive to provide competitive offers to successful candidates, new hire compensation is negotiable.
