Cloud Engineer – Azure Databricks

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🔥 0 minutes ago

🇲🇽 Mexico – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

☁️ Cloud Engineer

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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VALCE Talent Solutions

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🤝 B2B

🎯 Recruiter

💼 Consulting

B2B • Recruitment • Consulting

VALCE Talent Solutions is a company specializing in nearshoring, IT talent acquisition, and consultancy aimed at helping businesses expand globally, particularly in Mexico, LATAM, and the United States. They offer customized solutions that include talent recruitment, workforce management, and the integration of technology and artificial intelligence to enhance business processes. With a strong focus on strategic consulting, VALCE aims to connect technology, talent, and tangible results, boasting a robust network of IT professionals and a proven track record of successful placements and project scaling.

📋 Description

• Design, implement, and administer the Azure infrastructure foundation for an enterprise data and AI platform • Author and maintain reusable Terraform modules provisioning Databricks workspaces, ADLS Gen2, Data Factory, Key Vault, networking, and Azure ML • Own remote state, module versioning, drift detection, and infrastructure deployment pipelines • Design private networking and security architecture, including private endpoints, hub-and-spoke topology, VNet injection, NSGs, firewall rules, managed identities, RBAC, and data exfiltration controls • Own ADLS Gen2 storage architecture, ACLs, lifecycle and tiering policies, encryption, key management, and access patterns • Operate Azure Data Factory integration runtimes, linked-service credentials, managed identities, environment promotion, deployment automation, and monitoring • Provision and operate Azure ML workspaces, compute clusters, GPU capacity, MLflow model registry integration, model-serving endpoints, identity, and networking • Build and maintain observability using Azure Monitor, Log Analytics, diagnostic settings, alerting, and operational runbooks • Own FinOps visibility and optimization for DBU and storage spending, including tagging, chargeback/showback, budget alerts, reserved capacity, and capacity planning • Own CI/CD pipelines and promotion across development, test, and production • Establish Databricks account and workspace administration standards, topology, settings, role delegation, and multi-workspace strategy • Design Unity Catalog metastores, permissions, storage credentials, external locations, lineage, audit, and Delta Sharing • Manage Entra ID integration, SCIM, identity federation, groups, entitlements, service principals, and token policies • Define compute governance through cluster policies, instance pools, node/runtime standards, autoscaling, autotermination, Photon/serverless evaluation, and SQL warehouse configuration • Analyze system tables, usage attribution, and DBU forecasting to identify spend concentration and remediation paths • Review platform configurations, guide architecture decisions, publish standards and self-service patterns, and support administration and data teams • Diagnose job failures, cluster startup issues, permission errors, connectivity faults, and performance concerns across infrastructure, Databricks configuration, and workloads • Production ETL/ELT development, Spark transformations, model development, dimensional modeling, dbt, and BI/semantic-layer work sit with other teams

🎯 Requirements

• 6+ years in cloud infrastructure or platform engineering, with at least 4 years focused on Microsoft Azure • Expert-level, hands-on Terraform experience, including production Terraform modules, remote state, and CI/CD infrastructure as code • Demonstrable hands-on Databricks administration experience: account and workspace administration, Unity Catalog, cluster policies, identity federation, and cost governance • Track record as a senior technical resource to adjacent teams, guiding stakeholders and building consensus • Deep working knowledge of Azure networking and security: private endpoints, VNets, hub-and-spoke design, NSGs, Entra ID, managed identities, RBAC, and Key Vault • Enterprise-scale ADLS Gen2 design and access control • Azure Data Factory platform-side experience with integration runtimes, managed VNet, credential management, and deployment automation • Strong Python, plus PowerShell and/or Bash, for platform tooling and automation • Working knowledge of Spark and SQL for diagnosing infrastructure and configuration-level performance issues • Databricks Asset Bundles, Terraform Databricks provider, and workspace-as-code patterns preferred • Unity Catalog migration or multi-workspace consolidation experience preferred • Azure Machine Learning, MLflow, or model-serving infrastructure experience preferred • Kubernetes/AKS and containerized workloads preferred • Policy as code, event-driven infrastructure, formal FinOps practice, and multi-region or multi-tenant Databricks experience preferred • Certifications such as Databricks platform credentials, Azure certifications, or HashiCorp Terraform Associate preferred • Advanced English

🏖️ Benefits

• Remote work • Completamente remoto • Advanced English practice in a remote client environment