Senior Data and Back End Engineer

About

The organization is assembling a senior engineering cohort to accelerate Personal Loans Phase 2, focusing on building an abstraction layer and reliable data flows while core data remains with a partner. The team will include data engineers and back end engineers delivering Python, PySpark, Golang, and AWS-based solutions with an emphasis on fast, high-quality output. Work includes APIs, batch data pipelines, and standing up new infrastructure to make future data migrations transparent to downstream users. Candidates who leverage AI developer tools to improve productivity will align well with delivery expectations.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Responsibilities

• Design and implement an abstraction layer for data that remains with an external source, ensuring transparent future migration.
• Build and maintain APIs and batch data flows to support customer experiences and downstream consumers.
• Develop and optimize data pipelines using Python, PySpark, and big data frameworks on AWS.
• Stand up and harden back end services and cloud infrastructure, primarily in AWS.
• Deliver software increments quickly with reliable testing, monitoring, and documentation.
• Collaborate with cross-functional teams to integrate experiences from Personal Loans into the organization’s ecosystem.
• Leverage AI development tools to improve code quality, speed, and maintainability.
• Contribute to best practices for data engineering, security, and cost efficiency.

Experience Requirements

• Senior-level experience in data engineering with Python and PySpark.
• Hands-on experience with AWS big data tools and services such as EMR.
• Proficiency building APIs and batch data pipelines at scale.
• Strong back end engineering with Python or Golang and AWS.
• Experience standing up new cloud infrastructure and shipping software quickly.
• Familiarity with front end frameworks such as Angular or React (preferred).
• Experience using AI developer tools such as Claude or Windsurf to improve productivity (preferred).
• Prior experience within the organization’s environment or similar large-scale financial platforms (preferred).