BI Data Engineer - Platform Analytics

  • San Francisco, CA
  • Full-time

Company Description

When we launched the little white reader, we invented mobile, ubiquitous payments and enabled anyone to start, run, and grow a business. Ten years and billions of transactions later we’re reimagining commerce for businesses of all types and sizes—we’re enabling the independent electrician to send invoices, helping the beauty salon pay its employees, and giving the burgeoning coffee chain capital for a second, third, and fourth location. 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

As a Business Intelligence Data Engineer, you will be partnering with Platform Analytics team to architect, implement and manage Data Models and ETLs that curate product and event tracking data for fast and thorough analyses.  You will play an integral part in enabling the Platform Analytics team to take data-driven decision making and ROI optimization to the next level. You are a self-starter and you are comfortable working cross-functionally with other teams across Square.

You will:

  • Partner with various stakeholders in Platform Analytics, Marketing, Product Analytics and Data Science teams to understand their priorities, identify the right data sets to work on, understand their data and reporting requirements, and translate 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 company

  • Develop, deploy and maintain ETL jobs and visualizations

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

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

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



You have:

  • 5+ years working experience in a successful data engineering or business intelligence team

  • Expert knowledge in data modeling concepts and implementation

  • Strong technical accomplishments in SQL, ETLs and data analysis

  • Hands on experience in processing extremely large data sets.

  • Strong business intuition and ability to understand complex business systems

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

Even Better:

  • Familiarity with technologies such as Airflow

  • Experience with Snowflake database

  • Work experience with Python or any programming language

  • Experience with visualization technologies such as Looker 

  • Knowledge of payment network transactional data and event logging data

Additional Information

At Square, our purpose is to empower – within and outside of our walls. In order to build the best tools for the businesses and customers we support all over the world, we have to start at home with a workforce as diverse and empowered as our sellers. To this end, we take great care to evaluate all employees and job applicants equally, based on merit, competence, and qualifications. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply and always consider qualified applicants with arrest and conviction records, in accordance with 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) 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, Meal reimbursements, Wellness perks, Paid parental leave, Flexible time off, Learning and Development resources