Job description

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. As a Data Engineer, you'll guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you'll collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $130000 - $187000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . • Act as a trusted technical advisor to customers and solve complex Big Data and AI challenges. • Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. • Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform. • Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities. • Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities. • Bachelor's degree in Computer Science, a related field, or equivalent practical experience. • 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms. • Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams • Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL. Minimum qualifications: • Bachelor's degree in Computer Science, a related field, or equivalent practical experience. • 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms. • Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams • Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL. Preferred qualifications: • Google Cloud Platform (GCP) Professional Data Engineer Certification. • Experience building machine learning solutions and working with technical customers. • Experience in technical consulting and working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. • Experience building production LLM/GenAI systems: multi-agent orchestration, agent frameworks (e.g., ADK), tool and function calling, RAG, and prompt/context development. • Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.

Requirements

Must-haves

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Act as a trusted technical advisor to customers and solve complex Big Data and AI challenges.
Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.
Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
5 years of experience with data processing software (e.g., Spark, Beam) and algorithms.
Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams
Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL.
Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
5 years of experience with data processing software (e.g., Spark, Beam) and algorithms.
Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams
Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL.

Nice-to-haves

US: $130000 - $187000 (USD) + 15% bonus target + equity + benefits
Google Cloud Platform (GCP) Professional Data Engineer Certification.
Experience building machine learning solutions and working with technical customers.
Experience in technical consulting and working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
Experience building production LLM/GenAI systems: multi-agent orchestration, agent frameworks (e.g., ADK), tool and function calling, RAG, and prompt/context development.
Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aijavapythonsqlgcpmachine learningllm

Platform: google
Effort: medium