Role: DataOps Solution Architect — Azure Data Platform (Fabric & Databricks) Owns end-to-end architecture of the Azure data platform (Fabric, Databricks, Azure services) and sets the governance, security, and DataOps standards engineering teams implement. Design authority and primary architecture advisor to the client, not the day-to-day builder. Experience Required 8-10+ years overall in data engineering / cloud architecture, including 3+ years as a Solution Architect or in a comparable design-authority role. Microsoft Fabric: 2+ years hands-on. Azure Databricks: 4+ years hands-on. Proven track record designing and delivering enterprise-scale Azure data platforms end-to-end. Azure is mandatory ; experience across multiple client engagements or a consulting/SI background is a plus. Core Technical Expertise Azure Platform Fabric & Databricks architecture. ADF. ADLS. Entra ID. Key Vault. Monitor/Log Analytics. Microsoft Fabric Workspace & environment strategy. Lakehouse/Warehouse. OneLake. Pipelines/Notebooks. REST APIs/CLI. Governance. Azure Databricks Workspace strategy. Unity Catalog. RBAC. Jobs/Workflows. Delta Lake. Asset Bundles. ML platform integration. DevOps & IaC Azure DevOps/GitHub CI/CD. Terraform & Bicep. Branching/release strategy. Reusable IaC modules. Security & Networking Entra ID. RBAC architecture. Private Endpoints/DNS. Key Vault integration. DataOps Standards CI/CD & test gates for pipelines. Data-quality frameworks. Observability/alerting architecture. SLAs/SLOs. Incident-management practices. FinOps guardrails. Key Responsibilities Own end-to-end architecture; translate requirements into scalable, secure, cost-effective designs. Design enterprise-scale Fabric/Databricks architecture including workspace, networking, security, and governance. Set standards for CI/CD, IaC, DataOps, and environment management; ensure enterprise security and regulatory compliance. Evaluate technology options; identify architectural risks a
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About the Role We're looking for a FinOps Data Engineer to help drive cost optimization and cloud financial governance across our AWS infrastructure and GCP footprint. You'll work cross-functionally with Engineering, Finance, and Product to find and ship savings, build the tooling necessary to maximize efficiency of every dollar spent in the cloud, and cultivate a culture of cost awareness across engineering teams. This role owns the data side of that mission: the models, pipelines, and analysis that make cost, usage, and margin numbers trustworthy across the company. This is a hands-on engineering role, not an analyst seat. You'll do the schlep work other teams don't have time for, digging into a bucket's access pattern, writing the dbt model or Python pipeline that ships the fix, building the cost-vs-revenue mart that answers a margin question once instead of every time, and chasing a
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Department · Engineering
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Supabase
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