Senior Cloud Engineer, Databricks Platform - Hybrid or Remote

Location: Warren Township

Genesis
10 is currently seeking a Senior Cloud Engineer, Databricks Platform - for a Hybrid or Remote position with a Major Insurance Company located in Warren, NJ. This is a 5 month contract opportunity. We are seeking a Senior Cloud Engineer to design, implement, and administer the Azure infrastructure behind our enterprise data and AI platform. This is a cloud infrastructure and platform engineering position centered on Azure Databricks, ADLS Gen2, Azure Data Factory, and Azure Machine Learning.

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.

You should be equally at home provisioning a workspace through Terraform and advising on Unity Catalog design, cluster policy, or identity federation. 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.

Part One — Infrastructure Ownership:
Design, implement, and administer the Azure foundation the platform runs on. Infrastructure as Code (Terraform-first):
Author and maintain the reusable Terraform modules that provision the Azure data estate — Databricks work spaces, ADLS Gen2, Data Factory, Key Vault, networking, and Azure ML. Own remote state, module versioning, drift detection, and the pipelines that deploy them. Network & Security Architecture:
Design and implement the private networking and security posture for the platform — private endpoints, hub-and-spoke topology, VNet injection, NSGs and firewall rules, managed identities, Key Vault-backed secret scopes, RBAC, and data exfiltration controls. Data Lake

Infrastructure: Own ADLS Gen2 at the infrastructure layer: storage account architecture, hierarchical namespace, container and ACL strategy, lifecycle and tiering policy, encryption and key management, and access patterns for Databricks and downstream consumers. Data Factory Platform Operations:
Own ADF from the platform side — integration runtime provisioning and scaling (self-hosted and managed VNet), linked service credential and managed identity design, environment promotion, deployment automation, and monitoring. Pipeline development sits with the data engineering team. AI/ML Platform

Infrastructure: Provision and operate the infrastructure supporting machine learning workloads:
Azure ML work spaces and compute clusters, GPU quota and capacity planning, MLflow model registry integration, model serving endpoints, and the identity and networking connecting them to Unity Catalog. Observability & Reliability:
Build and maintain the monitoring layer — Azure Monitor, Log Analytics, diagnostic settings, alerting, and operational runbooks across the estate. Fin Ops & Capacity Planning:
Own cost visibility and optimization across DBU and storage spend — tagging strategy, chargeback and showback, budget alerts, reserved capacity, and forward capacity planning. CI/CD & Environment Management:
Own the deployment pipelines and promotion path across development, test, and production environments. Part Two — Databricks Platform Administration:
Day-to-day Databricks operations are supported by a dedicated administration team. This role establishes the platform standards and reference configurations that team works from, and serves as a senior technical partner on architecture, design decisions, and complex escalations. That partnership requires genuine administrative depth across the following areas. Account & Workspace Administration:
Account console configuration, workspace provisioning and topology decisions, workspace-level settings, admin role delegation, and multi-workspace strategy. Unity Catalog:
Metastore design and regional strategy,…