United States onlyPLUM 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.
Job Summary
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.
Key Responsibilities
- 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.
Preferred Qualifications
- 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.
