Customer Engineer, Data Analytics, Google Cloud (English, Korean)

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 4 years of experience with cloud native architecture in a customer-facing or support role.
  
• Experience with Big Data technologies like analytics warehousing, data processing, data transformation, data governance, data migrations, Extract, Transform, and Load (ETL), SQL, NoSQL, performance or scalability optimizations, or batch versus streaming.
• Experience with technical stakeholders and executive leaders.
• Ability to communicate in English and Korean fluently to interact in this customer-facing role.

Preferred qualifications:

• Experience in technical business or consulting in cloud computing, data analytics, or Big Data.
• Experience with developing data warehousing, data lakes, batch/realtime event processing, streaming, data processing, data migrations, data visualization tools and data governance on cloud native architectures.
• Experience with architecture design, implementing, tuning, schema design and query optimization of distributed systems.
• Experience in understanding customer requirements with the ability to break down requirements and design technical architectures.
• Experience with cloud computing (e.g., infrastructure, storage, platforms and data), with the cloud market and customer buying behavior.

About the job

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.

In this role, you will partner with technical business teams as a data analytics subject matter expert to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business tests, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks related to database migrations, data back ends and all aspects of the data lifecycle. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills.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.

Responsibilities

• Work with the team to identify and qualify business opportunities, understand key customer objections, and develop the strategy to resolve technical blockers, in relation to aspects of the data lifecycle.
• 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 partner 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 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 Request for Information (RFI) responses.