Data Engineer, Social Impact Data & AI Infrastructure

Google; Mountain View (CA); In loco; USD 130.000 - 187.000; Tempo pieno

Descrizione del lavoro

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.

Competenze

• 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.

Mansioni

• 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.

Conoscenze

Data infrastructure

Data modeling

ETL design

SQL queries

Formazione

Bachelor's degree or equivalent practical experience

Strumenti

Flume

DataFlow

Spark

Jupyter notebooks

Descrizione del lavoro

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.