Jobs at Databricks

Serve as trusted technical advisor for strategic accounts, design and build Databricks-based Lakehouse and GenAI/ML architectures, deliver proofs of concept, collaborate with sales/product/engineering, and support global account implementations and integrations across cloud environments.

Drive adoption of Databricks Genie across a regional territory through technical strategy, executive engagement, workshops, presentations, demos, and customer-facing collateral. Partner with Account Executives, GTM, Product, Engineering, GSIs, and consulting firms. Architect governed analytics solutions spanning semantic models, warehouses, metric layers, Lakehouse, and AI ecosystems; address governance and security concerns; resolve complex technical escalations; and provide roadmap feedback.

The Senior Big Data Engineer will manage customer engagements, develop big data architectures, and guide clients in utilizing the Databricks platform effectively.

Build trusted client relationships and demonstrate Databricks solutions through hands-on evaluations, Spark programming, proofs of concept, workshops, and technical presentations. Advise customers on big data analytics, solution architecture, data engineering, cloud integrations, and business value. Author reference architectures, how-to guides, and demo applications while developing toward independent Solutions Architect responsibilities.

Leads commercial delivery across complex enterprise data and AI/ML engagements, managing risks, scope, governance, reporting, customer outcomes, and cross-functional teams. Acts as a trusted advisor to senior stakeholders, supports account expansion, oversees statements of work and change control, protects margins, improves delivery practices, and mentors junior team members. The role requires strong cloud and modern data platform knowledge, executive communication, and experience managing Agile, Scrum, or hybrid delivery frameworks.

Manages and mentors a team of data engineers and architects, provides technical guidance, oversees customer Databricks projects, leads reusable tooling development, handles escalations, partners with stakeholders, improves service offerings, and supports customer success throughout sales and delivery.

Own the non-technical lifecycle of Field Deployment engagements: partner with sales to define C-suite value and MVPs, write PRDs, prioritize engineering backlogs, drive agile delivery, act as hands-on QA, manage launches and adoption, and scope ongoing maintenance while identifying growth opportunities.

The AI Engineer will develop and deploy GenAI applications, serve as a technical advisor, and collaborate on strategic initiatives in AI at Databricks.

Customer-facing engineering role delivering production-grade data and AI solutions on Databricks. Lead architecture, build end-to-end data pipelines, ML/AI integration, applications, and reusable assets. Collaborate cross-functionally, drive technical delivery, train and embed with customers, and contribute product and implementation feedback to scale impact.

Serve as the field product manager for FDE engagements: scope C-suite value, define pilot MVP and PRD, prioritize engineering backlog, run agile delivery, manage launch and adoption, and hand off ongoing maintenance and growth opportunities.

Customer-facing senior engineer who architects and delivers production-ready big data and AI solutions on Databricks across cloud platforms. Advises customers, builds reusable automation, designs reference architectures, supports migrations, and partners with engineering and support to drive product improvements and adoption.