Customer Engineer, Data Analytics, 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 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 sell new, highly specialized solutions to customers. You will solve analytics-centered customer challenges and provide a critical feedback loop to unblock customers and influence product development.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $153,000-$222,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or 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 business 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 working with ISVs.
• 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.