CF - Senior Backend Engineer - Python

About Empirical

Empirical empowers early and growth stage tech companies to create the right products in the right way by providing two pivotal services:

• Product & Technology Leadership: Our clients entrust critical decisions to our network of top-tier US-based CTOs and CPOs. We provide fractional, project, or advisory based support, combining highly experienced talent with a flexible approach.

• Product Development Teams: We provide our clients with high performing, senior product development talent through a scalable staff augmentation model and ongoing support. We focus on Latin America to find exceptional talent, with time zone and cultural compatibility.

We are proud to be a people first company, where we prioritize building meaningful, long lasting human connections with clients and team members alike, while embracing diversity and uniqueness. With this foundation and our focus on talent, we help create great products that people love.

Our values

• Care about people first

• Strive to add value always

• Lead with integrity

• Have fun every step of the way

The Opportunity

Our client is a fast-growing AI-powered digital lending platform entering a critical phase:

transforming their credit decisioning process through advanced financial data ingestion, credit bureau integrations, and unified data modeling.

They are looking for a Senior Financial Data Integrations Engineer with deep, hands-on experience in credit bureau, open-banking, and KYC/AML integrations.

This is not a generalist backend role — it requires expert-level domain knowledge of financial data, credit semantics, underwriting structures, and multi-provider data normalization.

You will design vendor-agnostic schemas, integrate with major financial data providers, and build the foundation of the company’s credit data layer.

What You’ll Do

Credit + Financial API Integrations

• Integrate directly with credit bureaus (Experian, TransUnion, Equifax)

• Build Python clients for open-banking / financial aggregation platforms (Plaid, Belvo, MX, MoneyThumb, Ocrolus, etc.)

• Implement secure API interactions following provider-specific compliance requirements

• Work with incomplete, inconsistent, or ambiguous third-party data and design mechanisms to reconcile discrepancies

Data Modeling & Normalization

• Design vendor-neutral schemas for credit reports, bank transaction data, and underwriting attributes

• Align heterogeneous financial datasets into unified internal representations

• Establish rules for cross-vendor field equivalency, transformations, and semantic consistency

• Develop automated validation checks and data quality controls to ensure accuracy across vendors

Backend Engineering (Python + FastAPI)

• Build and maintain high-quality FastAPI endpoints and internal services

• Implement async workflows for multi-provider data ingestion

• Ensure reliability, retries, and error handling across complex external APIs

• Optimize data ingestion performance across high-volume or low-latency financial workflows

Security, Compliance & Reliability

• Apply KYC/AML verification flows and regulatory constraints

• Handle PII securely, following encryption and data-handling best practices

• Collaborate on audit trails and traceability requirements for financial data

• Ensure compliance with data residency and cross-border data transfer requirements where applicable

Cross-functional Collaboration

• Work with AI, underwriting, and data teams to support real-time decisioning

• Contribute to roadmap planning around data ingestion, enrichment, and scoring pipelines

• Partner with product and compliance teams to refine provider selection and evaluate new financial data vendors

Your Qualifications

Required

• Strong proficiency in Python + Web Frameworks like FastAPI (Ideal), Django, or Flask

• Direct experience integrating with at least one major financial data provider:

  Experian, TransUnion, Equifax, Plaid, Belvo, MX, MoneyThumb, Ocrolus, Stripe Identity, etc.

• Deep understanding of credit/financial data semantics, including:

  • Credit reports

  • Tradelines

  • Bank transactions

  • Income/expense categorization

  • Underwriting attributes

• Hands-on experience designing vendor-agnostic data models

• Experience with data mapping, transformation rules, and schema normalization

• Comfortable working with async ingestion, retries, rate limits, and partial failure handling

• Working proficiency in English for technical discussions and cross-functional collaboration

• Experience working in distributed, remote-first teams

Nice to Have

• Knowledge of KYC/AML providers (e.g., Alloy, idwall, Persona)

• Experience with lending, risk modeling, scorecards, or underwriting systems

• Familiarity with fintech security / PCI / SOC2 constraints

• Experience with event-driven pipelines (Kafka, SQS, Pub/Sub)

• Experience working in U.S. startup environments or global fintech ecosystems

What we expect from you

• 100% alignment with our core values!

• Ability to take ownership of projects from start to finish

• Strong collaboration and communication skills

• Attention to detail and a passion for creating great user experiences

What we offer

• Remote/flexible work

• Highly competitive compensation in US dollars

• Opportunities for personal and professional development; mentorship, coaching and training as needed

• Ongoing, 40 hours per week dedication

• The chance to be part of an amazing, multicultural community of tech experts

Why work with us?

• We pride ourselves on our core values and have proven that putting people first creates a thriving and collaborative work environment.

• We seek to accommodate and balance individual needs with client needs, understanding each one of us is unique.

• We offer benefits such as remote/flexible work, selective paid training, mentorship programs, referral programs and more.

• We are selective in the projects we take on to ensure our teams are engaged in challenging, meaningful, enjoyable opportunities that will provoke creativity, innovation and growth!