Strategic Account Executive - Banking
Databricks Mosaic · London, United Kingdom
CHECKED 15H AGO
Infrastructureonsitesenior
At a glance
Highlights
- Drive big data and AI transformation for top Banking customers.
- Design unique use cases on Databricks Data Intelligence Platform.
- Co-develop business plans with ecosystem and cloud partners.
Ideal candidate
A seasoned enterprise seller with deep Banking relationships who thrives on solving complex problems with data and AI and motivating diverse teams to deliver customer transformation.
Requirements
- Experience in direct sales of enterprise software platforms to large enterprises
- Ownership of executive level relationships in your clients
- Proven track record of developing new business
- Extensive experience of working with large complex regulated organisations
- Knowledge of the Data & AI space with technology sales experience
- Longevity with previous employers
- Quota over-achievement and significant growth when selling complex software and services to Enterprise accounts
- Experience driving successful adoption of usage-based subscription services (SaaS) and co-selling with AWS, Azure and Google Cloud teams
- Methods for co-developing business cases and gaining support from C-level Executives
- Familiarity with sales methodologies and process (e.g Territory and Account planning, MEDDPICC, Challenger Sales and Command of the Message)
- Experience developing partnerships with champions and client teams to support execution of your territory plan
- Experience developing a clear partner strategy and implement it to achieve success
- Understanding of consumption-based, land and expand sales models advantageous
- Understanding of how to identify important use cases and buying centres to increase the impact of Databricks for clients
Lab profile
About Databricks Mosaic
Builds unified data analytics and AI platform to productionize AI applications.
What they build
- Databricks platform
- Unified Data Analytics and AI
- AI platform
Known for
- Forward-deployed AI engineering
- Productionizing first-of-kind AI applications
- Customer platform adoption and scale
- Cross-functional engineering and product collaboration