Company:
Google
Location: Seattle
Closing Date: 01/11/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Kirkland, WA, USA; New York, NY, USA; Seattle, WA, USA.
Minimum qualifications:
Google Cloud Data Analytics is a suite of services that helps people collect, store, process, and analyze data in the cloud. It includes a variety of tools and features that can be used to build data pipelines, create data warehouses, and run analytics queries. Google Cloud Data Analytics can be used to support a wide range of business use cases, from massive data-parallel batch pipelines to real time streaming data.
As the Principal Engineer of AI for Data and Analytics, you will be a critical leader responsible for driving the technical strategy and execution of integrating generative AI capabilities into Google Cloud's data analytics ecosystem. In this role, you will architect and deliver complex, high-impact systems. The services you will influence underlie some of the most critical products within Google Cloud's data analytics portfolio including Looker and BigQuery, offering a unique opportunity to define the future of data interaction and analysis and impacting millions of users by enabling unprecedented access to insights through the power of Gen AI.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 $278,000-$399,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 aboutbenefits at Google.
Responsibilities
Minimum qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 15 years of professional experience in software engineering.
- 10 years of experience working in data and analytics or Business Intelligence.
- Experience building and deploying large-scale systems in a cloud environment.
- Experience bringing tech products to market at a similar scale to that at which Google operates.
- PhD in Computer Science or similar field.
- Experience working with executive level internal and external clients/partners, acting as a representative of the company.
- Experience publishing in AI/ML conferences, demonstrating a deep understanding of the field and a commitment to advancing the state of the art.
- Ability to work cross-functionally, partnering with groups (e.g., Product Management, Product Marketing, UX, and UI), brokering trade offs with stakeholders and understanding their needs.
- Excellent narrative and storytelling abilities, communication skills, and presentation skills.
Google Cloud Data Analytics is a suite of services that helps people collect, store, process, and analyze data in the cloud. It includes a variety of tools and features that can be used to build data pipelines, create data warehouses, and run analytics queries. Google Cloud Data Analytics can be used to support a wide range of business use cases, from massive data-parallel batch pipelines to real time streaming data.
As the Principal Engineer of AI for Data and Analytics, you will be a critical leader responsible for driving the technical strategy and execution of integrating generative AI capabilities into Google Cloud's data analytics ecosystem. In this role, you will architect and deliver complex, high-impact systems. The services you will influence underlie some of the most critical products within Google Cloud's data analytics portfolio including Looker and BigQuery, offering a unique opportunity to define the future of data interaction and analysis and impacting millions of users by enabling unprecedented access to insights through the power of Gen AI.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 $278,000-$399,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 aboutbenefits at Google.
Responsibilities
- Define and execute the technical roadmap for generative AI within Google Cloud's data and analytics platform, aligning with the overall product strategy. Identify key opportunities, prioritize projects, and manage resources effectively to maximize impact across the portfolio.
- Collaborate closely with Product Management, UX Design, and Research teams as well as other Google Cloud teams to ensure alignment between technical capabilities and user needs, delivering seamless and intuitive user experiences across various data and analytics products.
- Stay at the forefront of advancements in generative AI, LLMs, and related technologies.
- Provide technical guidance, conduct code reviews, and support professional development to build a high-performing team.
- Lead the technical design and direction of generative AI features within Google Cloud's data and analytics ecosystem, architecting scalable and robust solutions leveraging LLMs for critical tasks.
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