Top Tech Jobs & Startup Jobs in Seattle, WA

The Senior Staff Partner Engineer will enhance the Built-On program's technical foundation by designing frameworks, collaborating with executives, and developing reference implementations, driving strategic alignment in platform development.

Oversee and motivate a sales team targeting VC-backed startups, focusing on new business acquisition and exceeding sales targets. Develop strategic plans, build relationships, and empower front-line sellers to communicate value effectively.

As a Senior Software Engineer, you'll manage billing systems for Databricks products, enhance infrastructure efficiency, and innovate pricing strategies using AI and big data.

The Engineering Manager will lead the Spark Structured Streaming team, overseeing development, recruitment, and adoption of Stream Processing technology. Responsibilities include managing technical debt, driving product vision, and fostering team growth.

This role involves enhancing security measures, leading engineering efforts in data security, and collaborating across teams to safeguard customer data.

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.

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

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

Design AI-native BI experiences that make analytics and generative AI intuitive, trustworthy, and actionable. Drive end-to-end product design from exploration to validation to action, collaborate with engineers and product, lead complex projects, engage strategic customers, and define new enterprise AI/BI design patterns.