We are seeking a highly experienced Lead Site Reliability Engineer to own and drive the reliability, scalability, and evolution of our enterprise observability platform.
This is not a traditional DevOps, Cloud Engineering, or Kubernetes-focused role. We are specifically looking for an engineer with deep hands-on expertise operating large-scale Elasticsearch, Logstash, Kibana (ELK) and Kafka platforms in mission-critical production environments. The successful candidate will serve as a technical leader, influencing architecture decisions, driving operational excellence, and mentoring engineering teams while remaining actively involved in troubleshooting and platform engineering.
You will work closely with Architecture, Engineering, Security, and Operations teams to ensure our observability and data ingestion platforms remain reliable, scalable, and performant.

• Lead the design, operation, maintenance, and continuous evolution of enterprise-scale Elasticsearch, Logstash, and Kibana platforms.
• Drive platform architecture, scalability planning, capacity management, and reliability improvements.
• Manage Elasticsearch cluster health, performance tuning, shard allocation strategies, index lifecycle management, and storage optimization.
• Plan and execute platform upgrades, migrations, patching activities, and disaster recovery initiatives.
• Investigate and resolve critical production incidents related to data ingestion, indexing performance, search latency, and cluster stability.
• Establish operational standards, monitoring frameworks, and best practices for observability platform operations.

• Design, operate, and optimize Kafka-based data ingestion pipelines supporting large-scale enterprise workloads.
• Troubleshoot data flow issues across Kafka, Logstash, Elasticsearch, and downstream consumers.
• Manage ingestion performance, throughput optimization, data retention, replay strategies, and platform resilience.
• Identify and eliminate bottlenecks across distributed ingestion architectures.
• Ensure end-to-end data reliability, consistency, and availability across production environments.

• Act as a technical authority for observability and platform engineering initiatives.
• Lead architecture reviews and challenge designs when necessary to ensure operational excellence.
• Drive technical decision-making through influence, collaboration, and engineering best practices.
• Partner with cross-functional teams to define scalable and maintainable platform solutions.
• Mentor engineers and contribute to the growth of technical capabilities across the organization.
• Simplify and communicate complex technical concepts to both technical and non-technical stakeholders.

• Lead root cause analysis for complex production incidents and implement sustainable preventive measures.
• Develop automation, monitoring, self-healing capabilities, and operational tooling.
• Drive continuous improvement initiatives across reliability, performance, security, and observability.
• Participate in critical incident response and post-incident reviews.
• Establish robust operational processes, documentation, and knowledge-sharing practices.

• Bachelor's Degree in Computer Science, Engineering, Information Technology, or a related discipline.
• 15+ years of experience in infrastructure engineering, platform engineering, site reliability engineering, or related enterprise technology environments.
• Demonstrated experience owning and operating large-scale production ELK platforms.
• Deep expertise in:
  • Elasticsearch
  • Logstash
  • Kibana
  • Kafka
• Strong understanding of:
  • Distributed systems architecture
  • High-availability platform design
  • Capacity planning
  • Performance tuning
  • Disaster recovery
  • Enterprise observability platforms
• Proven experience troubleshooting and optimizing large-scale Kafka ingestion pipelines
• Strong Linux administration and systems engineering knowledge.
• Experience automating operational processes using scripting and Infrastructure-as-Code practices.
• Ability to lead technical discussions across Architecture, Engineering, Operations, and Security teams.
• Excellent analytical, troubleshooting, and communication skills.

• 15+ years of overall experience in data engineering, data architecture, or analytics platform roles.
• 3+ years of experience in a senior or lead capacity, with accountability for architecture decisions and technical delivery.
• Demonstrated experience leading data engineering teams or acting as the primary technical authority for data platforms.
• Prior experience supporting banking, financial services, or regulated environments is strongly preferred.
• Proven track record of working with cloud-based data platforms (Databricks, AWS / Azure / GCP), including production-grade systems.
• Bachelor’s or Master’s degree in Computer Science, IT, Engineering, or a related technical field.
• Relevant certifications in cloud platforms, data engineering, or data architecture are an advantage