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Partner with customers and sales to design and present scalable Databricks Lakehouse architectures, build reference architectures and demos, consult on big data, ETL, and ML projects, validate integrations, and drive technical wins and adoption across accounts.

Lead the Engineering Team for Vector Search, developing a cloud-native service, managing team growth, and defining product roadmaps.

Design and automate networking for large-scale compute clusters, ensuring robust and scalable connectivity across cloud resources for data and AI workloads.

The Senior Staff Software Engineer will lead large-scale distributed system projects, mentor engineers, and drive company initiatives to deliver scalable and reliable software solutions.

As a Staff Software Engineer at Databricks, you will build and govern Money systems that enhance engineering efficiency, ensure reliable product availability, and collaborate with teams to scale infrastructure.

Sell Databricks to enterprise Media customers in Japan by acquiring new logos and expanding usage in existing accounts. Build C-level relationships, identify data use cases and buying centers, coordinate Databricks teams and partners, and drive account planning and negotiations to grow platform adoption.

The Staff Software Engineer will drive product innovation in distributed data systems, working on log analytics, AI/BI, data governance, and app development.

As a Senior Product Manager for Databricks Repos, you will define and drive the vision for the developer experience related to version control and workflow integration for data and AI applications.

Lead customer-facing data engineering and warehousing initiatives on the Databricks platform. Architect and optimize production-scale ETL/ELT pipelines, performance-test workloads, migrate legacy systems to cloud lakehouse architectures, support Solution Architects in technical sales, and provide training, demos, and community contributions.

Develop post-training recipes and systems for enterprise data agents capable of autonomous planning, code generation, and multi-step workflows. Partner with product teams to turn prototypes into production features for Databricks' Genie, and build context-discovery systems that use lakehouse data, notebooks, and code. Provide design, execution, debugging, and mentorship to raise team technical standards.