Data Engineer, GCS Data Science

The GCS Data Science team is working on challenging yet interesting problems for the GCS (Google Customer Solutions) division of Global Business Organization (GBO). Our goal is to build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.

The Data Science Engineering (DSet) subteam is responsible for supporting data engineering needs for the GCS Data Science teams including building new data pipelines, automation, observability and reporting tools.

As a Data Engineer, you will take on big data challenges in an agile way. In this role, you will use an analytical, data-driven approach to drive a deep understanding of our fast changing business. You will build data pipelines and reporting tools that enable our data scientists, through feature engineering, automated data extracts and wrangling needs, and scaled insights for both the data science team and our users.

Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you’ll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $106000 - $151000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

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.

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  
• 1 year of experience designing data pipelines (ETL) and model data.
• Experience analyzing data and creating reports, and with database query (e.g., SQL) and visualization tools (e.g., Tableau, dashboards).
  
• Experience with one or more general purpose programming languages (e.g., Python, C/C++, Java).
  

Preferred qualifications:

• Experience working in a data science environment, supporting feature engineering and model automation needs.
  
• Experience working with big data tools, distributed computing and non-relational databases.
  
• Structured thinking with ability to easily break down ambiguous problems and propose impactful data modeling designs.
  
• Passion for analyzing large and complex data sets and converting them into the information which drive business decisions.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA; San Francisco, CA, USA.

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.