Job Description
The Reconciliation Team oversees all money movement at Square, ensuring that our merchants, as well as external financial institutions, correctly settle with Square on every single transaction. We empower Accounting, Finance, Analytics, Payments, and product teams by delivering accurate data that is crucial to Squares financials and provides early warning indicators for many product systems at Square.
As a data warehouse developer on the Reconciliation team, you will be responsible for developing and managing curated datasets, key business metrics, and reporting. You will architect and implement data models and ETLs for reporting and investigating money movement across Squares products. You are a self-starter and you are comfortable working cross-functionally with other teams across Square. Together with teammates, you will write the next chapter of our teams data story.
You will:
Be an expert on the ins and outs of our products, customers, and data
Work alongside technical reporting analysts, product managers, and engineers to understand data and reporting requirements and lay the foundation for the analysis of our large, unique dataset
Provide data that is accurate, consistent, and useable by business users by designing and developing appropriate database objects and the processes used to populate those objects with data from internal and external sources
Design, develop, and implement robust alerting and data monitoring pipelines to ensure accuracy and completeness of Squares financial data
Build tools that help our data customers to extract, analyze, and visualize data faster
Develop and manage our current set of reporting tools and analytics infrastructure, seeking improvements where necessary
Perform ad hoc data analyses to resolve critical business issues
Evangelize data, analytics, and data model design best practices
Future proof our data warehouse to scale with the growth of the business
Qualifications
You have:
Bachelor's degree in a quantitative field, or equivalent work experience
6+ years of hands on experience processing and managing extremely large and complex datasets
Strong SQL (especially within cloud-based data warehouses like Snowflake, Google BigQuery), ETL (Airflow preferred), and data infrastructure skills
In depth knowledge of data warehouse design and query optimization
Experience building complex reporting and data monitoring processes for a variety of different business and product use cases
Experience with Linux/OSX command line, version control software (git), and general software development
Strong technical initiative and a desire to perform and grow as an individual
A love of data and a curiosity to consistently seek out new technologies
Strong business intuition and ability to understand complex business systems
Bonus points:
Experience with Looker
Experience with payments, financial data, accounting, or auditing
Experience with Python or Java
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)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.