Customer Engineer II – Data Analytics – Hcls – Google Cloud
| Company | |
|---|---|
| Location | San Francisco, CA, USA, Los Angeles, CA, USA, Irvine, CA, USA, Sunnyvale, CA, USA, Mountain View, CA, USA |
| Salary | $125000 – $183000 |
| Type | Full-Time |
| Degrees | Bachelor’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 in the Life Sciences.
- Experience with “Big Data” technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.
- Experience engaging with, and presenting to, technical stakeholders and executive leaders.
Responsibilities
- Work with the team to identify and qualify business opportunities related to aspects of the data life-cycle, understand key customer objections, and develop the strategy to resolve technical blockers.
- Share in-depth data analytics expertise 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.
- Identify business and technical requirements, conduct full technical discovery and architect client solutions to meet gathered requirements.
- Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
- Prepare and deliver business messaging in an effort to highlight the Google Cloud value proposition, using techniques such as whiteboard and slide presentations, product demonstrations, white papers and RFI responses.
Preferred Qualifications
- Experience in technical sales or consulting in cloud computing, data analytics, or Big Data.
- Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools and data governance on cloud native architectures.
- Experience with architecture design, implementing, tuning, schema design and query optimization of scalable and distributed systems.
- Experience with aspects of cloud computing (e.g., infrastructure, storage, platforms and data), as well as the cloud market, dynamics and customer buying behavior.
- Experience in understanding customer requirements with the ability to break down requirements and design technical architectures.