Customer Engineer II, Data Analytics, Google Cloud
About The Position
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. As a Practice Customer Engineer (CE) with a specialty in Data Analytics, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, to design data foundation architectures and develop MVPs (Minimum Viable Products) to promote new, highly specialized solutions to customers. You will solve analytics-centered customer issues and provide a critical feedback loop to unblock customers and influence product development. You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales expertise, market knowledge and direct technical engagement to prove the value of the Google Cloud portfolio.
Requirements
- Bachelor's degree or equivalent practical experience.
- 6 years of experience with cloud native architecture in a customer-facing or support role.
- Experience engaging with, or presenting to, technical stakeholders or executive leaders.
- Experience with Big Data technologies or concepts (e.g., analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, Spark, performance or scalability optimizations, batch versus streaming).
- Experience using programming languages (e.g., Python, Spark, SQL) to demo, prototype, or workshop with customers.
Nice To Haves
- Experience in technical sales or consulting in cloud computing, data analytics, and 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 cloud computing (e.g., infrastructure, storage, platforms, data) and the cloud market, participant dynamics, and customer buying behavior.
- Experience understanding customer requirements with the ability to break down requirements and design technical architectures.
Responsibilities
- Drive the technical win for complex workloads within Data Analytics to ensure rapid and successful adoption, primarily supporting the business cycle from use case identification, technical evaluation, and through customer ramp.
- Combine business strategies and direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
- Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships.
- Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team.
- Provide critical feedback from customer engagements to Product and Engineering teams to improve architectures and solutions. Work within Product and Engineering management systems to document, prioritize and drive resolution of customer feature requests and issues.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
