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Mid LevelFull-timePythonAWSGCPAzureKubernetesDockerTerraformAgileScrumCI/CD
Salary Range
$25,500 - $34,500 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking a DataOps Engineer to join Tech Delivery and Infrastructure Operations teams, playing a key role in ensuring the reliability, automation, and performance of our analytics and data platforms. This role combines elements of DevOps and SRE to sustain and optimize data-driven environments across global business units.
Key Responsibilities
- →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
Requirements
- ✓6 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)
