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Senior Data Engineer at Plum Inc. 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.. . . . 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.. . Company Location: United States.