Company Description

Square builds common business tools in unconventional ways so more people can start, run, and grow their businesses. When Square started, it was difficult and expensive (or just plain impossible) for some businesses to take credit cards. Square made credit card payments possible for all by turning a mobile phone into a credit card reader. Since then Square has been building an entire business toolkit of both hardware and software products including Square Capital, Square Terminal, Square Payroll, and more. We’re working to find new and better ways to help businesses succeed on their own terms—and we’re looking for people like you to help shape tomorrow at Square.

Job Description

Square is looking for a Data Engineer to join the Seller Customer Success Operations team to help define, develop and manage curated datasets, key business metrics and reporting. You will architect, implement and manage Data Models, pipelines and ETLs that will enable various teams access consistent metrics across the Customer Success ecosystem.

You will:

• Partner with functional leads to understand their data and reporting requirements, and translating them into definitions and technical specifications (PRD)

• Be responsible for defining, developing and optimizing curated datasets and schemas with standardized metrics and definitions across the the organization

• Be responsible for the data migration to new platforms and tools

• Develop, deploy, maintain, and optimize data models, pipelines, ETL jobs and visualizations

• Provide comprehensive day-to-day analytics support to partner teams, develop tools and resources to empower data access and self-service so your expertise can be leveraged 

• Model data in Looker or similar visualization tools, to empower data access and self-service resources so your expertise can be leveraged where it is most impactful

• Work closely with technical partners in the data platform engineering team on designing and developing robust data structures and highly reliable data pipelines

• Troubleshoot technical issues with platforms, performance, data discrepancies, alerts etc.

• Perform ad hoc analysis, insight requests, and data extractions to resolve critical business and infrastructure issues.

Qualifications

• 5+ years of analytical experience in data engineering, data science, or product / BI analytics

• Bachelor's degree required, with major in analytical or technical field strongly preferred

• Strong technical intuition and ability to understand complex business systems

• Expert knowledge in data modeling concepts and implementation

• Strong technical accomplishments in SQL, ETLs and data analysis skills

• MySQL, Snowflake, Redshift, or similar data handling experience

• Hands on experience in processing extremely large data sets

• Work experience with Python

• Experience with Linux/OSX command line, version control software (git), and general software development

• Expertise in visualization technologies including Looker, Tableau, and others

• Familiarity with scripting/programming for data mining and modeling is a plus

• Work experience with Java is a plus

Additional Information

At Square, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)squareup.com. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible.

Perks

At Square, we want you to be well and thrive. Our global benefits package includes:

• Healthcare coverage
• Retirement Plans
• Employee Stock Purchase Program
• Wellness perks
• Paid parental leave
• Paid time off
• Learning and Development resources