Lead Data DevOps Engineer (Azure Cloud)

We invite you to become our Lead Data DevOps Engineer with Azure Cloud to lead the architecture and advancement of our data infrastructure and workflows. You will be responsible for implementing scalable data solutions on Azure, collaborating closely with data engineers and other teams to maintain efficient pipelines and robust system performance. Take this opportunity to lead innovative cloud data initiatives. **Responsibilities** * Architect and operate data infrastructure using Azure services like Data Lake (ADLSv2\), Databricks, Synapse, and Data Factory * Collaborate with data engineering to develop and improve data pipelines and workflows * Enhance data operations automation through Python to increase efficiency and reliability * Manage and configure CI/CD pipelines with Jenkins, GitHub Actions, or equivalent tools * Work across teams to improve the scalability, reliability, and performance of data solutions * Deploy and maintain data tools such as Apache Spark and Apache Kafka in both cloud and on\-premises environments * Observe data system health and troubleshoot performance or scalability challenges * Address and solve complex issues with data pipelines and platforms **Requirements** * Five or more years of experience in Data Engineering or equivalent roles * At least one year experience in team leadership and management * Advanced proficiency with Python programming and batch workflows * Strong SQL skills for managing extensive datasets * Deep experience with Azure cloud services for data infrastructure * Experience using Infrastructure as Code tools including Ansible, Terraform, or CloudFormation * Competence in configuring CI/CD pipelines with Jenkins, GitHub Actions, or similar * Familiarity with data tools such as Spark, Airflow, or R * Advanced Linux system knowledge including scripting and administration * Comprehensive understanding of network protocols like TCP, UDP, ICMP, DHCP, DNS, and NAT * English language proficiency at B2 or above **Nice to have** * Exposure to other cloud platforms like AWS or GCP * Experience with Kubernetes container orchestration * Knowledge of monitoring and observability tools such as Prometheus, Grafana, or Azure Monitor * Experience with Big Data technologies and analytics workflows * Understanding of cloud data governance and security implementation