Dicetek LLC
Linkedin · Posted 15d ago
Site Reliability Engineer (SRE)
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Indexed description
What You Will Be Doing
- Define and implement SLIs / SLOs and error budgets for business-critical digital banking services.
- Build actionable observability (metrics, logs, traces, dashboards, and alerts) using Dynatrace, Prometheus, Grafana, and ELK, while reducing alert fatigue.
- Leverage AI-driven insights and anomaly detection (Dynatrace Davis AI or equivalent AIOps platform) to proactively predict and resolve reliability issues before impact.
- Lead incident management — from on-call triage and root-cause analysis to blameless postmortems with actionable follow-ups.
- Improve deployment safety with robust rollout / rollback strategies, canary and blue-green deployments, and production readiness reviews.
- Support and optimize microservices-based architectures, ensuring service reliability, scalability, and inter-service resilience.
- Conduct capacity planning, performance tuning, and resilience testing, optimizing for both reliability and cost efficiency.
- Automate operational toil — from runbooks and remediation scripts to proactive health checks and self-healing workflows.
- Collaborate with DevOps to embed reliability gates and validations into CI / CD pipelines (GitHub Actions, Jenkins, GitLab CI / CD or Azure DevOps).
- Own and evolve the observability and AIOps stack, driving intelligent automation and predictive alerting capabilities.
- Maintain high-quality documentation, playbooks, and operational standards across environments.
- Ensure operational compliance and security alignment with internal controls and regulatory standards.
- Analyze system performance, availability, and cost data to continually optimize operations.
- Provide reliability support and escalation guidance for critical production systems during major incidents.
- 5+ years of experience in SRE or DevOps roles, building and managing large-scale, high-availability systems across banking, fintech, e-commerce, or other data-intensive digital ecosystems.
- Bachelor’s degree in Computer Science or equivalent technical experience.
- Strong experience with Linux environments and performance troubleshooting.
- Proven expertise in Terraform and Infrastructure as Code (IaC) methodologies.
- Proficiency with Kubernetes and container orchestration in microservices environments.
- Hands-on experience with AWS (preferred); exposure to Azure or GCP is an advantage.
- Deep knowledge of Dynatrace (AIOps, Davis AI), Prometheus, Grafana, and the ELK stack.
- Experience implementing AI / ML-driven reliability or automation solutions (AIOps, anomaly detection, predictive alerting).
- Practical understanding of CI / CD pipelines (GitHub Actions, Jenkins, GitLab CI / CD or Azure DevOps).
- Experience with Kafka, RabbitMQ, Redis, Aurora, and RDS databases.
- Strong scripting or programming skills in Python, Bash, or Go. The Ideal Candidate
- Organized, structured, and meticulous in approach.
- Experienced in cross-functional collaboration and working with distributed teams.
- Strong analytical mindset with excellent troubleshooting skills for complex production systems.
- Calm and composed communicator under pressure, capable of leading during high-impact incidents.
- Proactive problem-solver who anticipates issues and drives preventive improvements.
- Passionate about AI-driven automation, observability, and reliability engineering.
- Continuously learning, keeping up-to-date with cloud-native, microservices, and SRE best practices.
- A collaborative and adaptable team player who thrives in a fast-paced, regulated environment and is passionate about building reliable, scalable systems that empower digital banking innovation.
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