Customer Engineer II – Business Intelligence – Google Cloud
| Company | |
|---|---|
| Location | San Francisco, CA, USA, Sunnyvale, CA, USA, Boulder, CO, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Senior |
Requirements
- Bachelor’s degree or equivalent practical experience.
- 6 years of experience with cloud native architecture in a customer-facing or support role.
- Experience selling or supporting business intelligence tools, and using them to manipulate datasets and databases (e.g., Looker).
- Experience engaging with, and presenting to, technical stakeholders and executive leaders.
Responsibilities
- Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
- Share in-depth Business Intelligence to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
- Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
- Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.
- Articulate and educate on technical and architectural concepts to a variety of audiences, including developers, architects, IT professionals, customers, partners and cross-functional team members.
Preferred Qualifications
- Master’s degree in Computer Science, Engineering, Mathematics, a technical field, or equivalent practical experience.
- Experience in prospecting, building and maintaining customer relationships from scratch, for building Greenfield territories in enterprise accounts.
- Experience in analyzing data with SQL, Python, or R with advanced data modeling and analytics.
- Experience in developing data warehousing, data lakes, batch or real-time event processing, and ETL workflow solutions.