Senior Data Engineer

Job Description

Job Description

PLUM is a fintech company empowering financial institutions to grow their business through a cutting-edge suite of AI-driven software, purpose-built for lenders and their partners across the financial ecosystem. We are a boutique firm, where each person’s contributions and ideas are critical to the growth of the company.

This is a fully remote position, open to candidates anywhere in the U.S. with a reliable internet connection. While we gather in person a few times a year, this role is designed to remain remote long-term. You will have autonomy and flexibility in a flat corporate structure that gives you the opportunity for your direct input to be realized and put into action. You'll collaborate with a high-performing team — including sales, marketers, and financial services experts — who stay connected through Slack, video calls, and regular team and company-wide meetings. We’re a team that knows how to work hard, have fun, and make a meaningful impact—both together and individually.

We are seeking a Senior Data Engineer to lead the design and implementation of scalable data pipelines that ingest and process data from a variety of external client systems. This role is critical in building the data infrastructure that powers Plum’s next-generation AI-driven products.

You will work with a modern data stack including Python, Databricks, AWS, Delta Lake, and more. As a senior member of the team, you’ll take ownership of architectural decisions, system design, and production readiness—working with team members to ensure data is reliable, accessible, and impactful.

• Design and architect end-to-end data processing pipelines: ingestion, transformation, and delivery to the Delta Lakehouse.
• Integrate with external systems (e.g., CRMs, file systems, APIs) to automate ingestion of diverse data sources.
• Develop robust data workflows using Python and Databricks Workflows.
• Implement modular, maintainable ETL processes following SDLC best practices and Git-based version control.
• Contribute to the evolution of our Lakehouse architecture to support downstream analytics and machine learning use cases.
• Monitor, troubleshoot, and optimize data workflows in production.
• Collaborate with cross-functional teams to translate data needs into scalable solutions.
  

Requirements

• Master’s degree in Computer Science, Engineering, Physics, or a related technical field or equivalent work experience.
• 3+ years of experience building and maintaining production-grade data pipelines.
• Proven expertise in Python and SQL for data engineering tasks.
• Strong understanding of lakehouse architecture and data modeling concepts.
• Experience working with Databricks, Delta Lake, and Apache Spark.
• Hands-on experience with AWS cloud infrastructure.
• Track record of integrating data from external systems, APIs, and databases.
• Strong problem-solving skills and ability to lead through ambiguity.
• Excellent communication and documentation habits.

• Experience building data solutions in Fintech, Sales Tech, or Marketing Tech domains.
• Familiarity with CRM platforms (e.g., Salesforce, HubSpot) and CRM data models.
• Experience using ETL tools such as Fivetran or Airbyte.
• Understanding of data governance, security, and compliance best practices.

Benefits

• A fast-paced, collaborative startup culture with high visibility.
• Autonomy, flexibility, and a flat corporate structure that gives you the opportunity for your direct input to be realized and put into action.
• Opportunity to make a meaningful impact in building a company and culture.
• Equity in a financial technology startup.
• Generous health, dental, and vision coverage for employees and family members + 401K.
• Eleven paid holidays and unlimited discretionary vacation days.
• Competitive compensation and bonus potential.