Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together.

To solve this problem, we expanded into software and built integrated solutions to help sellers sell online, manage inventory, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale.

Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.

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.

You have:

• 2+ 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
• 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
• Experience with Linux/OSX command line, version control software (git), and general software development
• Strong experience in visualization technologies including Looker, Tableau, or others
• Familiarity with scripting/programming for data mining and modeling is a plus
• Work experience with Python and Databricks is a plus