Build, configure, and operate Databricks workspaces, clusters, policies, and supporting Azure services
Enable a clear path to production environments, including operational processes, runbooks, incident response practices, and release readiness
Support and harden ETL/ELT pipelines (e.g., Delta Lake patterns), job orchestration, and workload performance tuning
Implement infrastructure-as-code and CI/CD practices for Databricks and related Azure resources (e.g., Terraform/Bicep, Azure DevOps/GitHub)
Implement least-privilege access, secrets management, identity integration, auditability, and compliance-aligned controls
Improve logging, monitoring, and cost controls; diagnose and resolve platform/network issues affecting delivery
Participate in Madrid-based team stand-ups and planning; manage an agreed backlog of tasks that unblock AI for ALL and analytics delivery.

5+ years experience in cloud/platform engineering (preferably Azure)
2+ years hands-on experience with Databricks (Azure Databricks strongly preferred)
Strong hands-on experience operating Azure Databricks in enterprise settings
Working knowledge of Spark, Delta Lake, Python and SQL
Experience with networking/security patterns in Azure (VNETs, private endpoints, Key Vault, managed identities, etc.)
Experience with IaC (Terraform, ARM/Bicep) and CI/CD for platform and data workloads
Familiarity with AWS/GCP concepts
Experience with Unity Catalog
Experience supporting data governance patterns and lineage/metadata tooling
Familiarity with GenAI workload considerations.

Cloud Engineer, Data Platforms

Key skills