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PayJoy is a mission-driven Public Benefit Corporation providing secured credit solutions to underserved customers in emerging markets. The company has served over 18 million customers as of 2025 and operates profitably with advanced machine learning, data science, and anti-fraud AI capabilities.
As Senior Analytics Engineer, you will own PayJoy's data governance and analytics infrastructure at scale. Your responsibilities include:
• Design and operate the Unity Catalog governance model, including catalog and schema architecture, tagging and metadata standards, lineage, access grants, and PII controls. Your goal is to make data access auditable and self-evident to analysts rather than tribal knowledge.
• Define and enforce standards that make data trustworthy by default: implement tiered certification standards strong enough for regulated reporting, establish service-level objectives for high-traffic data products, and build robust alert detection while retiring duplicate and abandoned models.
• Own the governed semantic layer and transformation development loop, ensuring conformed dimensions, canonical entity keys, and single definitions for cross-functional measures. This enables different teams asking the same question to get the same answer, supports AI-assisted analysis with sound semantics, and allows new contributors to ship correct models in their first week.
• Establish PayJoy's experimentation framework by owning the measurement substrate (experiment metric definitions, exposure tables, guardrail metrics, readout correctness) and advising on tooling, statistical approach, and instrumentation architecture with Product Engineering.
• Deliver scoped enablement projects whose primary output is a reusable pattern that becomes a standard for others to build against.
Requirements:
• Bachelor's degree in a related field or equivalent; Master's degree preferred
• 10+ years of experience in data analytics and engineering
• Deep data governance expertise on a modern lakehouse (e.g., Unity Catalog or equivalent at multi-catalog scale): schema architecture, metadata and tagging strategy, lineage, grants, row- and column-level security. You must have designed a governance model, not just worked within one.
• Expert-level data modeling expertise with defensible positions on test strategy, incremental model semantics, and when a model should not exist
• Track record of driving adoption of a standard, tool, or platform that changed behavior across teams outside your reporting line
• Strong communication skills to explain complex analytical concepts to technical and non-technical audiences
• Comfortable working in ambiguous, high-impact environments with broad scope and autonomy
