Remote Python Backend Engineer: Financial Data Integrations

Pomona College; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote-first

Flexible PTO

401(k) plan

Medical, dental, and vision coverage

Job summary

Cardiff, Inc. is seeking an experienced Python backend engineer to own the financial data integration layer. You will build FastAPI services and provider integrations (Experian, Plaid, bank feeds), and manage AWS/ETL pipelines feeding Snowflake. This contract role evolves toward full-time as you prove impact, data quality, and security.

You will implement automated validations, document data models, and explore LLM-assisted extraction with proper validation before data enters the pipeline.

Qualifications

• 5+ years of Python backend engineering on data-intensive systems.
• Production backend services with FastAPI or similar frameworks.
• Reliable third-party API integration with retries and observability.
• Substantial Snowflake experience in production.
• AWS data services for orchestration and data lakes; SQL and Pandas.

Responsibilities

• Design, build, and run FastAPI services exposing financial data to internal users.
• Own integration layer with external providers: retries, rate limits, credentials.
• Build pipelines landing provider data in Snowflake using serverless ETL on AWS.
• Data modeling and schema mapping with domain experts and analysts.
• Implement LLM-assisted extraction with validation before pipeline entry.
• Maintain unit/integration tests and documentation for all components.

Skills

Python

API design

Data modeling

SQL

Pandas

Tools

Snowflake

FastAPI

AWS Lambda

Glue

Athena

Step Functions

S3

Job description

Cardiff, Inc. is seeking an experienced Python backend engineer to own the financial data integration layer. You will build FastAPI services and provider integrations (Experian, Plaid, bank feeds), and manage AWS/ETL pipelines feeding Snowflake. This contract role evolves toward full-time as you prove impact, data quality, and security.

You will implement automated validations, document data models, and explore LLM-assisted extraction with proper validation before data enters the pipeline.