Job Description

Job Description
Looking for a professional to manage and support data pipelines and analytical platforms, ensuring that information is reliable, accurate and accessible. The position involves working with ETL processes, monitoring, automation and incident support within cloud data environments.
Responsibilities:
Manage and maintain data pipelines and ETL processes, ensuring the quality and availability of information.
Perform data validations, quality checks, and performance optimization using SQL and Python or Shell scripts.
Implement monitoring and observability with tools such as Datadog, Grafana and Prometheus to monitor the health and performance of systems.
Integrate data deployments into CI/CD processes using Jenkins, Azure DevOps and Git, in collaboration with the DevOps and Infrastructure teams.
Apply infrastructure as code principles with Terraform and Ansible to provision and automate data environments.
Provide support in the management of incidents and requests through ServiceNow, ensuring compliance with SLAs and performing analysis.
Collaborate with security and compliance teams to maintain data protection and governance standards.
Requirements:
5+ years of experience in DataOps, data engineering operations, or analytics platform support, with knowledge of DevOps/SRE practices.
Proficiency in SQL and scripting in Python or Shell for automation and data diagnosis.
Experience with cloud platforms (AWS required, Azure or GCP is a plus).
Knowledge of CI/CD tools (Jenkins, Azure DevOps), version control (Git), and infrastructure as code frameworks (Terraform, Ansible).
Experience with monitoring tools such as Datadog, Grafana or Prometheus.
Understanding containerization concepts with Docker and Kubernetes.
Knowledge of governance, observability and data quality standards.
Experience in incident management and tracking operational metrics such as MTTR, uptime and latency.

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