Practice Customer Engineer, Data Analytics, Startups, Google Cloud

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 Cloud AI, you will partner with technical sales teams as a data analytics subject matter expert to differentiate Google Cloud to our startup 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 be writing code to develop prototypes, proofs-of-concept, and demos to sell new, highly specialized solutions to customers. You will solve AI-centered customer challenges and provide a critical feedback loop to influence product development.

You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and present solutions on Google Cloud. You will blend sales expertise, market knowledge, and technical engagement to prove the value of the Google Cloud portfolio.

It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $152000 - $221000 (USD) + 42.86% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Drive the technical win for complex workloads within Data Analytics to ensure rapid and successful adoption, primarily supporting the sales cycle from use case identification, technical evaluation, and through customer ramp.
• Combine sales 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.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing or support role.
• 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 engaging with, or presenting to, technical stakeholders or executive leaders.
• Experience using programming languages (e.g., Python, Spark, SQL) to demo, prototype, or workshop with customers.

Preferred qualifications:

• 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 understanding customer requirements with the ability to break down requirements and design technical architectures.
• Experience with cloud computing (e.g., infrastructure, storage, platforms, data) and the cloud market, competitive dynamics, and customer buying behavior.