Senior Data Engineer

About Donorbox Donorbox is a leading fundraising platform and donor management system for nonprofit organizations. Our mission is to accelerate positive impact worldwide by helping nonprofits become highly effective at raising funds and managing their supporter base. Since 2014, we have powered more than 100,000 global organizations to raise over $4 billion in donations. Our fast-growing company is profitable and bootstrapped with a healthy run rate. We have a fully distributed and diverse 150-person team based in 16+ states and 23+ countries. In 2026, Donorbox was named by Built In as one of the Best Places to Work in Washington, DC. Donorbox is rated the #1 software for fundraising, donor management, and nonprofit payment on G2 based on hundreds of verified customer reviews — a reflection of the care our team puts into building products that nonprofits trust. The Role Donorbox is looking for a motivated and collaborative Data Engineer to join our growing team. You'll play a key role in building and maintaining the data infrastructure that powers our analytics and helps drive critical decisions across the organization. If you're passionate about data, enjoy solving complex problems, and thrive in a dynamic environment, we'd love to hear from you! Responsibilities - Develop and Maintain Data Pipelines: Design, build, and optimize robust ETL/ELT workflows using SQL , Python , dbt , and Airflow to ingest and process data from various sources. - Design and Optimize Data Models: Create and refine data models, primarily within BigQuery , ensuring they are efficient, scalable, and support our analytical and reporting needs. - Ensure Data Quality and Usability: Cleanse, transform, and structure data to ensure accuracy, consistency, and a format suitable for analysis and reporting. - Mentor and Collaborate: Serve as a technical leader, mentoring junior engineers and promoting best practices in coding, data modeling, and system design. You’ll also work closely with data analysts and business stakeholders to translate business needs into technical requirements.

- Build Reporting Foundations: Support the creation of summary tables and enhance database models to provide Data Analysts with ready-to-use data for their work. - Document Everything: Maintain clear and concise documentation for data systems, pipelines, data flows, and schemas, making it easy for others to understand and utilize our data assets. - Deploy Data Products: Help deploy datasets, reports, and dashboards to Superset for wider consumption. - Practice Software Engineering Excellence: Follow best practices in software development, including version control , testing , and modular code design. - Work in an Agile Environment: Operate effectively within our agile development framework, contributing to continuous improvement and quick iterations. - Present and Gather Feedback: Engage with stakeholders to present completed data products and gather valuable feedback for further iterations. - Own the Solution: Take ownership of complex data problems from start to finish, from identifying the root cause to implementing a production-ready solution. - Conduct regular performance audits on existing data pipelines, databases, and dashboards, and implement optimizations. Qualifications & Experience - Experience: 5+ years of hands-on experience in a Data Engineering role, with a proven track record of building and managing production data systems. - Technical Proficiency: - Strong proficiency in SQL , Python , dbt , and Airflow . - Extensive experience with PostgreSQL and Google Cloud Platform . - Familiarity with Superset or other visualization tools like PowerBI, Tableau, ... - Software Engineering Principles: A solid understanding of core software engineering principles, including modular code design, testing, and version control (e. g. , Git).