Data Engineer at Donorbox

Donorbox is looking for a motivated and collaborative Data Engineer to join their growing team. You’ll play a key role in building and maintaining the data infrastructure that powers their analytics and helps drive critical decisions across the organization.

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 analytical and reporting needs.
• Ensure Data Quality and Usability: Cleanse, transform, and structure data to ensure accuracy, consistency, and usability 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. 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.
• Document Everything: Maintain clear and concise documentation for data systems, pipelines, data flows, and schemas.
• 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 an agile development framework, contributing to continuous improvement and quick iterations.
• Present and Gather Feedback: Engage with stakeholders to present completed data products and gather 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, etc.
• Software Engineering Principles: A solid understanding of core software engineering principles, including modular code design, testing, and version control (e.g., Git).
• Problem-Solving Skills: The ability to think critically, solve complex problems independently, and drive projects to completion.
• Communication: Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Agile Experience: Experience working in an agile development environment.

Bonus Points if You Have:

• Experience working with Ruby.
• Experience in the nonprofit or fundraising technology sector.
• Experience with SaaS.