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Job Summary

We are looking for a highly skilled and motivated Senior SRE to join our team. As an Enterprise Data & Analytics Platform Production Support Engineer is responsible for ensuring the operational stability, reliability, and availability of enterprise data, analytics, streaming, and integration platforms.

This role works closely with Platform SRE, Platform Engineering, Data Engineering, Integration, CloudOps, and Security teams to resolve production issues, coordinate response during incidents, and support ongoing reliability and operational excellence initiatives.

Responsibilities

Production Support & Operations

• Monitor platform health across data pipelines, APIs, streaming platforms, and cloud services
• Triage, investigate, and resolve production incidents and service requests
• Execute and improve operational runbooks and standard operating procedures
• Coordinate incident resolution across Platform Engineering, SRE, Data Engineering, and external vendors
• Support release activities, configuration changes, and production validations
• Participate in incident reviews and contribute to problem management activities

Incident, Problem & Change Management

• Own incident lifecycle activities including detection, communication, resolution, and closure
• Perform root cause analysis (RCA) and contribute to preventive and corrective actions
• Identify recurring issues and work with SRE and engineering teams to reduce operational toil
• Ensure adherence to incident, problem, and change management processes and SLAs

Observability & Monitoring

• Use monitoring and logging tools to detect anomalies and performance degradation
• Improve alert quality by reducing noise and improving signal-to-noise ratio
• Work with SRE to refine dashboards, alerts, and operational metrics
• Support SLIs/SLOs from an operational execution perspective

GenAI-Driven Support Optimization

• Leverage GenAI / LLM-based tools to improve production support efficiency and quality
• Use AI-assisted analysis for:
  • Faster log analysis and incident triage
  • Pattern detection across recurring incidents
  • Root cause hypothesis generation
• Contribute to building and maintaining AI-powered support assistants (e.g., Platform GPT) for:
  • Runbook recommendations
  • Knowledge retrieval and troubleshooting guidance
  • Incident summarization and post-incident reporting
• Identify opportunities where GenAI can reduce manual effort in:
  • Incident analysis
  • Knowledge management
  • Support documentation
  • Alert enrichment and contextualization
• Partner with Platform Engineering to operationalize AI-enabled support workflows safely and responsibly

Collaboration & Continuous Improvement

• Act as a key interface between Production Support, SRE, and Platform Engineering
• Provide operational feedback to influence platform design for better supportability
• Maintain clear documentation of incidents, known issues, and operational procedures
• Mentor junior support engineers and promote operational best practices
• Participate in platform readiness and operational reviews

Qualifications

Experience

• 8–10+ years of experience in Production Support, Platform Operations, SRE, AIOps roles supporting enterprise platforms

Technical Skills

• Strong experience supporting cloud-based data and analytics platforms and services (GCP preferred, AWS)
• Hands-on operational experience with:
  • Data platforms and pipelines
  • API platforms (e.g., Apigee, GKE etc.,)
  • Streaming systems (Kafka, Pub/Sub)
• Familiarity with monitoring and observability tools (Grafana, Prometheus, ELK, Cloud Monitoring)
• Working knowledge of CI/CD pipelines and release processes
• Strong troubleshooting skills across distributed systems
• Expertise in containerization and orchestration technologies like Docker and Kubernetes
• Experience in infrastructure as code (IaC) using tools like Terraform

GenAI & Automation

• Practical experience using GenAI/LLM tools (e.g., ChatGPT, Gemini, internal LLM platforms) for operational use cases
• Ability to apply AI tools to improve:
  • Incident response
  • Knowledge discovery
  • Operational documentation
• Familiarity with automation and scripting (Python, shell, or similar)
• Understanding of responsible AI usage, data privacy, and security considerations in production environments

Methodologies & Practices

• Knowledge of incident, problem, and change management frameworks (ITIL-aligned)
• Understanding of SRE concepts such as SLIs, SLOs, and error budgets (execution-focused)
• Experience working in agile, DevOps-oriented environments

Soft Skills

• Strong analytical and problem-solving skills
• Calm, structured communicator during high-severity incidents
• Excellent coordination and stakeholder management abilities
• Continuous improvement mindset with an interest in automation and AI-driven efficiency

Preferred Qualifications

• Experience supporting enterprise-scale data warehouses (BigQuery etc.)
• Exposure to AI/ML operations or data platform governance
• Experience contributing to internal tooling, knowledge bases, or support automation frameworks

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability.  If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer.  All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. 

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