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We are hiring a Lead Data DevOps Engineer with Azure to lead the design and optimization of data infrastructure and workflows on Azure. You will manage scalable data solutions and collaborate with data engineering and cross-functional teams to ensure pipeline efficiency, system stability, and performance improvements. Join us to play a pivotal role in advancing our cloud data capabilities.
Responsibilities

Develop and manage data infrastructure using Azure services including Data Lake (ADLSv2), Databricks, Synapse, and Data Factory
Collaborate with data engineering teams to build and enhance workflows and data pipelines
Automate data processes with Python to improve reliability and operational efficiency
Set up and maintain CI/CD pipelines with Jenkins, GitHub Actions, or other tools
Work with cross‑functional teams to improve data system scalability, reliability, and performance
Configure and maintain data tools like Apache Spark and Apache Kafka across cloud and on‑premises environments
Monitor data platform performance and resolve any scalability or performance issues




Troubleshoot and fix complex technical problems related to data platforms and pipelines

Requirements

At least 5 years of experience in Data Engineering or related fields
Minimum 1 year of experience leading development teams
Advanced Python programming expertise and batch processing workflow experience
Strong SQL abilities for managing large datasets
Extensive experience with Azure cloud services for data infrastructure
Hands‑on experience with Infrastructure as Code tools such as Ansible, Terraform, or CloudFormation
Proficiency in managing CI/CD pipelines with Jenkins, GitHub Actions, or similar
Experience with data processing tools like Spark, Airflow, or R
Advanced Linux OS knowledge including scripting and system administration
Strong understanding of network protocols including TCP, UDP, ICMP, DHCP, DNS, and NAT
Fluent English at B2+ level

Nice to have

Knowledge of other cloud platf

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