Manage and support data pipelines, ETL processes, and analytics platforms, ensuring reliability, accuracy, and accessibility
Execute data validation, quality checks, and performance tuning using SQL and Python/Shell scripting
Implement monitoring and observability using Datadog, Grafana, and Prometheus to track system health and performance
Collaborate with DevOps and Infra teams to integrate data deployments within CI/CD pipelines (Jenkins, Azure DevOps, Git)
Apply infrastructure-as-code principles (Terraform, Ansible) for provisioning and automation of data environments
Support incident and request management via ServiceNow, ensuring SLA adherence and root cause analysis
Work closely with security and compliance teams to maintain data governance and protection standards
Participate in Agile ceremonies within Scrum/Kanban models to align with cross-functional delivery squads

5+ years in DataOps, Data Engineering Operations, or Analytics Platform Support, with good exposure to DevOps/SRE practices
Proficiency in SQL and Python/Shell scripting for automation and data diagnostics
Experience with cloud platforms (AWS mandatory; exposure to Azure/GCP a plus)
Familiarity with CI/CD tools (Jenkins, Azure DevOps), version control (Git), and IaC frameworks (Terraform, Ansible)
Working knowledge of monitoring tools (Datadog, Grafana, Prometheus)
Understanding of containerization (Docker, Kubernetes) concepts
Strong grasp of data governance, observability, and quality frameworks
Experience in incident management and operational metrics tracking (MTTR, uptime, latency)

DataOps Engineer

Key skills