Note: The job is a remote job and is open to candidates in USA. Techgene Solutions is seeking a Senior Cloud Engineer to support its enterprise data and AI platform. The role designs, implements, and administers Azure infrastructure centered on Azure Databricks, ADLS Gen2, Azure Data Factory, and Azure Machine Learning, while owning infrastructure as code, network and identity architecture, compute governance, observability, and cost management. The engineer will partner with Databricks administration, data engineering, and data science teams to define platform standards, reference architectures, and technical solutions.
Responsibilities
- We are seeking a Senior Cloud Engineer to design, implement, and administer the Azure infrastructure behind our enterprise data and AI platform
- You will own the platform foundation - infrastructure as code, network and identity architecture, compute governance, observability, and cost management - and partner closely with our Databricks administration, data engineering, and data science teams
- Our group defines the platform standards and reference architectures those teams build within, which means depth in Databricks administration matters here as much as depth in Azure
- This role suits an engineer who enjoys being the technical reference point for a platform: setting the architectural direction, partnering with adjacent teams on complex problems, and translating business requirements into the platform capabilities needed to support them
- Day-to-day Databricks administration is handled by a dedicated team; this role provides the standards, architecture, and senior technical partnership behind it
Skills
- Experience: 6+ years in cloud infrastructure or platform engineering, with at least 4 years focused on Microsoft Azure
- Terraform: Expert-level, hands-on. You have authored and maintained production Terraform modules, managed remote state, and run infrastructure as code through CI/CD
- Databricks Administration: Demonstrable hands-on administration experience - account and workspace administration, Unity Catalog, cluster policies, identity federation, and cost governance. You should be able to describe administrative decisions you have made and explain the tradeoffs behind them
- Technical Partnership: A track record as a senior technical resource to adjacent teams, including guiding stakeholders from an initial request to the underlying requirement and building consensus around the recommended approach
- Azure Networking & Security: Deep working knowledge of private endpoints, VNets and hub-spoke design, NSGs, Entra ID, managed identities, RBAC, and
- Key Vault
- Data Lake Architecture: ADLS Gen2 design and access control at enterprise scale
- Azure Data Factory: Platform-side experience with integration runtimes, managed VNet, credential management, and deployment automation
- Automation & Scripting: Strong Python, plus PowerShell and/or Bash, for platform tooling and automation
- Spark & SQL Literacy: Sufficient working knowledge to diagnose infrastructure and configuration-level performance issues and engage credibly with data teams. Spark development depth is not a requirement for this role
- Databricks Asset Bundles, the Terraform Databricks provider, and workspace-as-code patterns
- Experience leading a Unity Catalog migration or multi-workspace consolidation
- Azure Machine Learning, MLflow, or model-serving infrastructure experience
- Kubernetes / AKS and containerized workloads
- Policy as code - Azure Policy, OPA, Sentinel, or Checkov
- Event-driven infrastructure - Event Hubs, Kafka, or Stream Analytics
- Formal FinOps practice experience
- Multi-region or multi-tenant Databricks deployments
- Databricks Certified Data Engineer Professional, or a Databricks platform administrator credential
- Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
- Microsoft Certified: Azure Administrator Associate (AZ-104)
- Microsoft Certified: DevOps Engineer Expert (AZ-400)
- HashiCorp Certified: Terraform Associate
Benefits
- 100% Remote, USA
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