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NEXTMOVEFDE careers · United States

Staff Partner Engineer, Azure

Technologies

Azure · Python · SQL · infrastructure-as-code · API integration · Databricks · Microsoft Azure · Cursor · Claude Code · Codex

About Databricks

Unified Data Intelligence Platform (lakehouse + Mosaic AI) used by 10,000+ orgs and 50%+ of the Fortune 500 for ETL, BI, ML, and GenAI.

Private Late

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Production engineering · Evidence for this classification:

RDQ427R371 At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role We're seeking a Partner Engineer to own the technical relationship between Databricks Product/Engineering and Microsoft Azure. You will be the primary technical liaison managing our cross product roadmap, driving
More from the job description

RDQ427R371 At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role We're seeking a Partner Engineer to own the technical relationship between Databricks Product/Engineering and Microsoft Azure. You will be the primary technical liaison managing our cross product roadmap, driving engineering integrations, and ensuring Databricks products work seamlessly within the Azure ecosystem. You will work directly with Azure Partner SAs, Product Managers, and engineering teams to align roadmaps, identify integration gaps, and accelerate feature delivery. This role reports to the Director of Partner Engineering and works closely with Databricks Product Management, Engineering, and Field teams. Impact you will have Own the Databricks-Azure product-to-cloud technical roadmap, serving as the pr [... source excerpt omitted ...] erence implementations for Azure + Databricks solutions. Enable field teams with technical guidance on Azure-Databricks integration patterns, working with Solution Architects and Customer Success to accelerate Azure customer wins. What we’re looking for 10+ years of experience in cloud solution architecture, partner engineering, or technical program management roles, with deep expertise in Microsoft Azure services and architecture patterns. Proven experience managing strategic technical partnerships at VP/C-level, with ability to navigate complex multi-company engineering initiatives and drive consensus across organizations. Hands-on technical skills with ability to prototyp [... source excerpt omitted ...] -term partnership health. Deep knowledge of Databricks platform and Microsoft data/AI ecosystem Excellent communication and influence skills, with ability to translate technical requirements between Product Management, Engineering, and external partner teams. Preferred Prior experience in Partner Solutions Architect or Alliance Engineering roles at cloud providers (AWS, Azure, GCP) or major ISVs. Background working at or with Microsoft - understanding of Microsoft field organization, partner program structure, and decision-making processes. History of driving product-to-product integrations between major platforms. Familiarity with modern development workflows and AI-assisted

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