Mandatory Skills: Python/R and ML libraries (scikit-learn, TensorFlow, PyTorch), Data analysis and visualization (Pandas, NumPy, Power BI/Tableau), SQL and database management
Key Responsibilities
Monitor, maintain, and improve the reliability, availability, and performance of production systems.
Design and implement monitoring, alerting, logging, and observability solutions.
Establish and track Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Error Budgets.
Automate operational tasks and repetitive processes using scripting and Infrastructure as Code (IaC).
Lead incident response activities, troubleshooting, root cause analysis (RCA), and post-incident reviews.
Collaborate with development, infrastructure, and platform teams to improve system reliability and resilience.
Perform capacity planning, performance tuning, and scalability assessments.
Support CI/CD pipelines and deployment automation initiatives.
Implement high-availability, disaster recovery, and failover strategies.
Required Skills
Strong experience with Linux/Unix administration.
Proficiency in scripting languages such as Python, Shell, or PowerShell.
Hands‑on experience with cloud platforms (AWS, Azure, or GCP).
Experience with containerization technologies such as Docker and Kubernetes.
Knowledge of monitoring and observability tools such as Prometheus, Grafana, ELK, Splunk, Dynatrace, or Datadog.
Understanding of CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
Experience with Infrastructure as Code tools such as Terraform, Ansible, or CloudFormation.
Strong troubleshooting, debugging, and problem-solving skills.
Understanding of networking, security, and distributed systems concepts.
Experience
5–10+ years of overall IT experience.
5+ years of hands‑on experience in Site Reliability Engineering, Production Support, DevOps, or Cloud Operations roles.