Business Analytics Specialist

About PayJoy

PayJoy, a Public Benefit Corporation, is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success. Our patented technology for secured credit provides an on-ramp for new customers to enter the credit system. Through PayJoy’s point-of-sale financing and card offerings, customers gain access to a modern quality of life. PayJoy’s credit also allows our customers to seize opportunities as micro-entrepreneurs, and acts as insurance for tough times. Through our cutting-edge machine learning, data science, and anti-fraud AI, we have served over 18 million customers as of 2025 while achieving solid profitability for sustainable growth.

This role

Data Architecture

Own and evolve the Bronze / Silver / Gold data architecture for the Global Metrics ecosystem.

Define scalable architectural patterns for integrating new Customer Support platforms and data sources.

Design dimensional, relational, and analytical data models.

Define standards for data ingestion, transformation, storage, and consumption.

Design integration patterns across APIs, cloud storage, SaaS platforms, and enterprise data platforms.

Establish architecture principles for data quality, traceability, lineage, scalability, and maintainability.

Partner with Data Engineering teams to translate architectural designs into production-ready implementations.

Review technical solutions and ensure alignment with Global Metrics architectural standards.

Data Pipelines & Large-Scale Processing

Design scalable data pipelines using Databricks and dbt.

Work with large-scale datasets and high-volume data ingestion workloads.

Define transformation patterns and data-processing strategies for distributed environments.

Optimize data models and processing pipelines for performance, scalability, reliability, and cost.

Support ingestion strategies using platforms such as Fivetran, APIs, file-based integrations, and cloud object storage.

Define reusable patterns for batch and incremental data processing.

Ensure pipelines are designed with appropriate monitoring, recoverability, and data-quality controls.

Analytics & Semantic Architecture

Own the design and evolution of the analytics semantic layer.

Define scalable frameworks for KPIs, business metrics, dimensions, and analytical entities.

Translate business concepts into standardized analytical definitions and data models.

Design and govern the Gold analytical layer used by dashboards, analytics, AI, and reporting.

Define dimensional and OLAP models optimized for analytical consumption.

Establish reusable semantic models to reduce duplicated business logic across dashboards and datasets.

Partner with Business Analysts and stakeholders to ensure metrics accurately represent business processes and operational reality.

Metrics Governance & Business Rules

Define and maintain standards for KPI definitions, calculations, dimensions, and business rules.

Maintain and evolve the business glossary and data dictionary.

Establish governance processes to prevent conflicting or duplicated metric definitions.

Define global naming conventions, taxonomies, tags, classifications, and analytical standards across Customer Support platforms.

Ensure business definitions are consistently translated into technical implementations.

Support the definition of global analytical entities such as customers, contacts, interactions, tickets, agents, queues, channels, and support journeys.

System & Data Integration Architecture

Define how new systems and vendors are integrated into the Global Metrics data ecosystem.

Evaluate integration alternatives such as APIs, event streams, file exports, object storage, managed ingestion platforms, and direct database connections.

Define source-of-truth strategies and relationships across multiple operational systems.

Design data models that enable end-to-end traceability across Customer Support interactions and platforms.

Participate in architecture discussions with internal Data, Engineering, Security, and Platform teams.

Work with vendors and technical stakeholders to assess data availability, integration capabilities, and architectural constraints.

AI & Advanced Analytics Architecture — Preferred

Education

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Statistics, or a related technical field.

Equivalent professional experience may be considered in place of formal education.

Experience

3+ years of experience in Data Engineering, Analytics Engineering, Data Architecture, Business Intelligence Architecture, or similar roles.

Proven experience designing and implementing scalable analytical data solutions.

Strong hands-on experience with:

Databricks

dbt

Advanced SQL

Dimensional data modeling

Data warehouse / lakehouse architectures

Medallion Architecture (Bronze / Silver / Gold)

Semantic layers and analytical data models

Data integration patterns

Experience working with large-scale datasets and high-volume data ingestion is required.

Experience designing and optimizing scalable data pipelines.

Experience with Fivetran or equivalent managed ingestion platforms is preferred.

Experience with Spark and distributed data processing is strongly preferred.

Experience designing analytics solutions consumed by BI platforms such as Hex, Tableau, Power BI, Looker, Mode, or equivalent tools.

Familiarity with:

LLM-based analytics

Context engineering

NLP / text analytics

AI data pipelines

Data-Centric AI principles

AI / Advanced Data Experience — Nice to Have

100% Company-funded Health for employees and immediate family members

Life Insurance

Indefinite-term contract

20 days of vacations, unlimited sick leave

$2,000 USD annual Co-working Travel perk

$2,000 USD annual Professional Development perk

Phone finance, headphone benefit, home office equipment allowance and wellness perks

Catered lunches

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