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As a Sr. Staff Technical Solutions Engineer, you will provide specialized support to Databricks' strategic customers, solve technical challenges, and optimize performance using Spark and data technologies.

Drive revenue realization and enablement at scale across a portfolio of accounts by designing repeatable workflows, building lightweight automations, analyzing activation and usage trends, identifying friction, and continuously improving processes and tooling to increase customer adoption and efficiency.

You will drive the vision and roadmap for Databricks Repos, defining integration with Git services and enhancing user workflows for data and AI teams.

Lead the engineering team in developing next-generation ETL features for Databricks Lakeflow. Oversee recruitment, manage technical debt, and ensure high-quality infrastructure services.

The AI Engineer will develop and deploy GenAI applications, collaborate with teams, and present at conferences, leveraging strong technical skills and industry experience.

Design AI/BI product experiences that make natural-language data queries and AI-generated insights intuitive, transparent, and actionable. Lead end-to-end design from exploration to validation and action, collaborate with product and engineering, define AI-native enterprise patterns, and influence long-term AI/BI strategy.

Sell Databricks' Data Intelligence Platform into enterprise telco accounts by building executive relationships, expanding footprint, driving pipeline and revenue, and managing forecasts and customer details in Salesforce. Advocate AI/Big Data solutions, prioritize opportunities, and exceed quotas while collaborating internally and with system integrators.

The role focuses on enhancing customer data security, leading security engineering initiatives, and promoting data security practices throughout the organization.

As a Staff Data Scientist, you'll drive data-driven insights, mentor junior staff, and integrate data science tools with engineering teams. You'll lead critical projects and represent data science in various settings.

Design and automate networking foundations for large-scale compute clusters. Lead development of secure, scalable connectivity across cloud providers to support data and AI workloads.