Data Engineer, Google.org for Social Impact

Google; Mountain View (CA); On-site; USD 130,000 - 187,000; Full time

Job summary

Google.org's Tech for Social Impact (TSI) team builds data infrastructure and analytics tools to accelerate social outcomes. The role focuses on harmonizing data across nonprofit partners and internal systems to enable reliable reporting and AI-enabled insights.

Assemble scalable data pipelines, govern data quality, and collaborate with stakeholders to deliver on-time projects while advancing non-profit impact through responsible data science and enterprise-grade dashboards.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 3 years of experience coding in one or more programming languages.
• 3 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
• 3 years of experience designing data pipelines and dimensional data modeling for synch and asynch system integration using internal and external stacks.

Responsibilities

• Define the architecture and technical solution for a harmonized data infrastructure, leading complex ETL constraints across both internal and external Google.org data systems.
• Develop a harmonized data repository and algorithmic data infrastructure solutions that simplify reporting and visualization across Google.org data tools.
• Execute zero-downtime data migrations with shadow testing and automated rollback checkpoints.
• Build well-structured data assets and tables powering dashboards and self-service AI-powered BI analytics tools.
• Implement AI-assisted data validation workflows.

Skills

Data infrastructure

Data modeling

ETL design

SQL queries

Education

Bachelor's degree or equivalent practical experience

Tools

Flume

DataFlow

Spark

Jupyter notebooks

Job description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 3 years of experience coding in one or more programming languages.
• 3 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
• 3 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).

Preferred qualifications:

• 3 years of experience with statistical methodology and data consumption tools such as business intelligence platforms and Jupyter notebooks.
• 3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
• 3 years of experience developing project plans and delivering projects on time within budget and scope.
• Experience with Machine Learning for production workflows.
• A passion for social impact, philanthropy, and empowering nonprofits and civic entities through data.

About the job

The Google.org Tech for Social Impact (TSI) team works to accelerate sustained social impact through technology. We do this by supporting Google.org and the wider ecosystem of nonprofits and civic entities through data infrastructure, data visualization tools, and products that help them accomplish their missions.

The TSI team leads the work to unify Google.org's data and operational workflows into a single, trusted source of truth across global giving. By building a harmonious data repository, integrating partner records and CRM workflows, and powering AI-enabled business intelligence and workflow automations, we eliminate administrative friction and enable both data-driven human decision-making and safe, reliable AI autonomy across our philanthropic portfolio.

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.

Responsibilities

• Define the architecture and technical solution for a harmonized data infrastructure, leading complex ETL constraints across both internal and external Google.org data systems.
• Develop a harmonized data repository and algorithmic data infrastructure solutions that simplify reporting and visualization across Google.org data tools.
• Execute zero-downtime data migrations with shadow testing and automated rollback checkpoints.
• Build well-structured data assets and tables powering dashboards and self-service AI-powered BI analytics tools.
• Implement AI-assisted data validation workflows.

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