DataOps Engineer (Azure, Python)

Your 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

Our requirements

• 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+