Teams at Databricks

Build and productionize data and AI solutions for federal customers using Databricks. Own architecture, design decisions, data pipelines, ML/AI integrations, and user-facing applications. Lead technical delivery, advise customers, integrate client systems, provide training, and collaborate with engineering, product, support, and project teams. Contribute reusable frameworks and best practices while managing complex stakeholder relationships and delivering secure, scalable production systems.

Customer-facing senior engineer who architects, implements, and productionizes end-to-end data and AI solutions on Databricks. Responsibilities include Spark-based distributed data engineering, ML/AI model integration, CI/CD deployments, technical project delivery, stakeholder engagement, reusable assets creation, and providing product/implementation feedback.

Own customer-facing AI and data engagements from discovery through production launch. Define business value, MVPs, success criteria, and product requirements; prioritize engineering backlogs; lead technical discovery, architecture reviews, agile delivery, testing, production readiness, launch, adoption, and strategic handoff. Build C-suite relationships, translate business needs into technical requirements, resolve delivery risks, and identify future high-value opportunities.