Data Engineer: ML Pipelines, Dashboards & Equity

Google Inc.; New York (NY); On-site; USD 106,000 - 151,000; Full time

Benefits offered by this job

Equity

Bonus target 15%

Job summary

Google Inc. in New York, NY, is seeking a Data Engineer to join the GCS Data Science Engineering (DSet) team. You will build data pipelines and reporting tools to empower data scientists and drive scalable insights for advertisers.

The role emphasizes feature engineering, ETL automation, data wrangling, and collaboration with stakeholders to transform large, complex datasets into actionable business recommendations.

Qualifications

• Bachelor's degree in CS or related field or equivalent practical experience.

Responsibilities

• Build data pipelines, reports, best practices and frameworks that enable analysts and other stakeholders across the organization.
• Use feature engineering to support data needs for ML/AI model development and subsequent scaling through ETL pipeline development.
• Recognize and adopt best practices in developing pipelines, analytical insights including data integrity, test design, analysis, validation and documentation.
• Design and develop scalable and actionable solutions (dashboards, automated collateral, web applications) that tell a story and provide insights to help our advertisers grow.
• Work closely with various stakeholders to understand feature/tooling gaps and innovate on behalf of our customers.

Skills

ETL

Data pipelines

SQL

Python

Java

C/C++

Education

Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience

Tools

Tableau

Dashboards

Job description

Google Inc. in New York, NY, is seeking a Data Engineer to join the GCS Data Science Engineering (DSet) team. You will build data pipelines and reporting tools to empower data scientists and drive scalable insights for advertisers.

The role emphasizes feature engineering, ETL automation, data wrangling, and collaboration with stakeholders to transform large, complex datasets into actionable business recommendations.