Full-Time Staff DataOps Engineer

• Total experience: 7+ years
• Extensive experience in DataOps, Data Engineering Operations, or Analytics Platform Support
• Strong exposure to DevOps/SRE practices.
• Proficiency in SQL and Python/Shell scripting for automation and data diagnostics.
• Hands-on experience with cloud platforms (AWS mandatory; Azure/GCP is a plus).
• Familiarity with CI/CD tools (Jenkins, Azure DevOps), version control (Git), and Infrastructure-as-Code frameworks (Terraform, Ansible).
• Working knowledge of monitoring tools (Datadog, Grafana, Prometheus).
• Understanding of containerization concepts (Docker, Kubernetes).
• Strong grasp of data governance, observability, and quality frameworks.
• Experience in incident management and operational metrics tracking (MTTR, uptime, latency).

• 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 Infrastructure 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.
• Bachelor’s or master’s degree in computer science, Information Technology, or a related field

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