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PayJoy is a mission-driven Public Benefit Corporation providing credit solutions to underserved customers in emerging markets. The company uses proprietary technology for secured credit, point-of-sale financing, and card offerings to help customers achieve financial stability and access opportunities as micro-entrepreneurs. With cutting-edge machine learning, data science, and anti-fraud AI capabilities, PayJoy has served over 18 million customers while maintaining profitability.
As an Analytics Engineer, you will play a critical role in building and maintaining the data infrastructure that powers PayJoy's credit decisioning, risk management, and customer insights. You'll work at the intersection of data engineering and analytics, designing scalable data pipelines, building analytical models, and creating self-service analytics tools for business stakeholders.
Key responsibilities include: designing and implementing ETL/ELT pipelines to ingest, transform, and load data from multiple sources; building data warehouses and data marts optimized for analytics and reporting; collaborating with data scientists on feature engineering and model deployment; creating dashboards and analytics tools that drive business decisions; ensuring data quality, governance, and security; and optimizing query performance and data infrastructure costs.
You'll partner closely with product, risk, finance, and operations teams to understand their analytical needs and translate them into scalable technical solutions. This role requires strong SQL and Python skills, experience with cloud data platforms (Snowflake, BigQuery, or Redshift), and familiarity with modern data stack tools. Experience with financial services, credit risk, or fraud detection is a plus.
