Senior Data Engineer

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. 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.