Google

Runs Search and YouTube and builds Gemini AI

AI Data Developer 2 - Professional Services

Data EngineeringConfirmed live in the last 24 hours

Full-timeToronto, ON, CanadaIn-person

About the Job

Requirements

A Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
At least five years of experience with data processing software such as Spark or Beam and algorithms.
Experience managing client-facing projects, troubleshooting technical issues, and working with Developers and Sales Services teams.
Experience with database administration techniques or distributed data processing, and writing software in Java, Python, or SQL.

Responsibilities

Act as a trusted technical advisor to customers and solve complex Big Data and AI challenges; communicate effectively for client meetings and onsite delivery activities.
Lead end-to-end delivery of enterprise-scale data platforms, enabling real-time ingestion and high-performance consumption for AI/ML and Agentic use cases.
Own the operational lifecycle of data products, including governance, security, cost-efficiency, and SLA management, in collaboration with stakeholders to drive long-term technical strategy.
Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring the approach and messaging to varied levels of business and technical stakeholders.
Analyze on-premises and cloud data platform environments and consult on optimal design for performance and deployment on Google Cloud Platform.
Guide customers on ingesting, storing, processing, analyzing, exploring, and visualizing data on Google Cloud Platform.
Lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges.
Collaborate with Google's strategic cloud customers and internal teams to implement Google Cloud products successfully.

Desired Qualifications

Google Cloud Platform Professional Data Certification(s).
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, including multi-agent orchestration, agent frameworks such as ADK, tool and function calling, RAG, and prompt/context development.
Experience architecting, developing software, or building internet-scale production-grade Big Data solutions in virtualized environments.
Experience building machine learning solutions and working with technical customers.

Act as a trusted technical advisor to customers and solve complex Big Data and AI challenges. Communicate effectively for client meetings and onsite delivery activities. Travel up to 30% of the time.
Lead the end-to-end delivery of enterprise-scale data platforms, enabling real-time ingestion and high-performance consumption for AI/ML and Agentic use cases.
Own the operational lifecycle of data products—including governance, security, cost-efficiency, and SLA management—in collaboration with stakeholders to drive long-term technical strategy.
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 data platform environments and consult on the optimal design for performance and deployment on Google Cloud Platform.

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 Developers and Sales Services teams
Experience with database administration techniques or distributed data processing, as well as writing software in Java, Python, or SQL.

Preferred qualifications:

Google Cloud Platform (GCP) Professional Data Certification(s).
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.
Experience building machine learning solutions and working with technical customers.

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 Developer, 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.

Canada: $170000 - $174000 (CAD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.This posting is for an existing vacancy.

Google utilizes AI tools to assist in assessing candidates in our hiring processes.

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 Developers and Sales Services teams
Experience with database administration techniques or distributed data processing, as well as writing software in Java, Python, or SQL.

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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