Practice Customer Engineer, Data Analytics, Google Cloud
Indexed description
Minimum qualifications:
- Bachelor's degree in a technical field or equivalent practical experience.
- 10 years of experience in a customer-facing technical role or equivalent engineering experience, with a focus on data analytics and cloud solutions.
- Experience with core data analytics and Big Data concepts (e.g., analytics warehousing, data transformation, ETL/ELT pipeline design, SQL, and database performance optimizations).
- Experience using programming languages (e.g., Python, Java, Go) to build technical prototypes, demonstrations, or proof-of-concepts for customers.
- Experience presenting technical architectures to technical stakeholders and executive/C-level business leadership.
- Master's degree in Computer Science, Engineering, Mathematics, or a technical field.
- Experience working with LLMs and designing agentic workflows and multi-agent architectures.
- Experience in managing and delivering successful proof-of-concepts, focused on the customer value provided by the solution and meeting customer needs.
- Expertise with distributed systems, Lake House architectures, Spark/Dataproc, MLOps, schema design, and query optimization.
- Expertise with advanced data modeling and analytics.
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.
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
- Drive the technical win for complex workloads within data analytics to ensure rapid, successful adoption, supporting the business cycle from use case identification and technical evaluation through customer ramp.
- Combine sales strategies and prototyping to deliver tailored solutions across the end-to-end data lifecycle—encompassing storage, transformation, and visualization—securing buy-in from customer domain experts.
- Design and architect advanced analytics experiences, specifically incorporating modern technologies like AI-driven data agents and analytic agents to meet evolving enterprise demands.
- Lead complex migrations and proof-of-concepts, helping enterprise customers transition legacy data environments to modern Google Cloud solutions.
- Drive internal technical leadership and feedback loops, partnering with GTM to build reusable solutions and collaborating with Product/Engineering to escalate and resolve customer feature requests.
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