Senior Python Developer

Job Title: Senior Python Developer

Reports to: Lead Machine Learning Engineer

Intelligent Audit is a rapidly expanding freight audit and business analytics technology company helping our customers become smarter shippers – shipping to their customers faster, cheaper, and with fewer delivery exceptions. We leverage big data and sophisticated analytics to remove inefficiencies in global transportation spend.

As a Senior Python Developer, you will build and maintain backend systems focused on automating internal processes and supporting the Data Science team. Your primary responsibility will be developing scalable web scraping solutions and data pipelines to extract, transform, and load data from multiple external sources. You will use AI coding assistants and agents throughout the software development lifecycle to accelerate delivery, improve code quality, and automate repetitive engineering work, while maintaining ownership of technical decisions and production outcomes.

What You Will Do:

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The individual with this position in our company will be expected, on a regular basis, to:

Process Automation & Backend Development

• Design and develop automated systems for internal process optimization.
• Build scalable backend services that integrate with existing infrastructure.
• Ensure services are reliable, performant, and maintainable.

Web Scraping & Data Extraction

• Develop and maintain web scraping solutions for multiple external websites.
• Handle dynamic content, rate limiting, authentication, and anti-scraping measures.
• Implement robust error handling, logging, and retry mechanisms.

Data Manipulation & Processing

• Clean, transform, and process large volumes of structured and unstructured data.
• Build and maintain data pipelines to deliver usable datasets to downstream systems.

Monitoring & Observability

• Implement monitoring for system performance, data quality, and operational metrics (e.g., Datadog).
• Create dashboards and alerts to ensure system reliability and data integrity.

Data Science Team Support

• Provide backend infrastructure, data pipelines, and tooling for Data Science projects.
• Collaborate with data scientists to deliver data and services that enable experimentation and model deployment.

Code Quality & Best Practices

• Apply test-driven development and maintain solid unit/integration test coverage.
• Perform code reviews using engineering judgment and AI-assisted review tools to identify defects, security issues, and maintainability concerns.