technologies-expected :

responsibilities :

Design, implement, and maintain CI/CD pipelines for data workflows to enable rapid, reliable deployments
Drive observability and testing within data pipelines to ensure quality, uptime, and compliance with SLAs
Build reusable abstractions and platform components that simplify development for data teams
Apply SRE principles to ensure scalability, reliability, and resilience across distributed data systems
Collaborate on cost optimization and governance of cloud-based data infrastructure.
Partner with data engineers, DevOps, and infrastructure teams to standardize data delivery and operations
Enable data mesh architecture, managing workspace setup, deployment, and lifecycle for data product teams
Create clear documentation and onboarding materials to help data teams deploy and operate independently
Facilitate cross-team communication between data, DevOps, and security groups to ensure cohesive platform practices

requirements-expected :

Minimum 5 years in similar position
Strong background in Azure Cloud (Data Factory, Databricks, Azure SQL, Synapse)
Hands-on experience with Python, PowerShell, and Terraform (IaC) for automation and infrastructure management
Experience in data pipeline orchestration, monitoring, and CI/CD for data (Azure DevOps, GitHub Actions)
Familiarity with data governance, lineage, and cataloging (Unity Catalog or similar)
Understanding of distributed data systems, data mesh principles, and scalable architectures
Solid communication skills and experience working in cross-functional, collaborative teams Nice to Have
Exposure to ML/AI data pipelines or model deployment workflows
Experience in SRE or platform engineering roles supporting data infrastructure
Understanding of cost management and optimization in large-scale Azure environments
English: B2+