Migration Architect
•Omni· 2h
EngineeringFull-time$170k-210kUS Only
2h ago
Donorbox·about 1 month ago
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 close to $3B 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.
🏅Donorbox is rated the #1 software for fundraising, donor management, and nonprofit payment on G2 based on hundreds of verified customer reviews. We're proud of what we do, and our product reflects it!
Our data team is at the heart of this mission, providing the insights that inform product decisions and guide our business strategy as we scale our impact for nonprofits worldwide.
We are seeking an experienced Engineering Manager to lead our data engineering team and own our modern data stack. This is a critical player-coach role for someone who is equally passionate about people leadership and hands-on technical work.
You will manage and mentor a talented team of data engineers while serving as the primary owner of our data infrastructure (DBT, Airflow, Superset, PostgreSQL). You’ll set the technical direction, ensure data quality and reliability, and continuously improve how data is built, validated, and delivered across the company.
If you enjoy building scalable data infrastructure, fostering a collaborative team culture, and holding a high bar for data accuracy, this role is for you.
Agile Management: Organize and lead two-week sprints, including sprint planning, bi-weekly check-ins, and ownership of the team’s Kanban board.
Foster Collaboration: Promote transparency and shared ownership by enforcing strong peer-review practices for all DBT, Airflow, and related pull requests.
Report & Communicate: Clearly communicate team progress, key metrics, and strategic initiatives to leadership and cross-functional stakeholders.
Strategic Roadmap: Define and execute the long-term vision for Donorbox’s data engineering infrastructure, with a focus on scalability, performance, and reliability.
Process & Governance: Establish and document workflows, data priorities, access controls, and the full development lifecycle (PR → Staging → Test → Main → Production).
Data Stack Management: Take full ownership of our data stack, including:
DBT: Review all PRs for code quality, performance, model structure, and data correctness; act as the final checkpoint for accuracy.
Airflow: Build, manage, and troubleshoot DAGs for data imports, scheduling, and pipeline reliability.
Superset: Validate data accuracy and performance across reports and dashboards before handoff to the Data Analytics team for UAT.
PostgreSQL: Maintain, optimize, and scale our Postgres data warehouse, which serves as the source of truth for analytics and reporting.
Python: Write and review Airflow DAGs to ingest external data sources and improve existing pipelines.
Data Modeling: Design and guide scalable data models to support a growing set of dashboards, reports, and analytical use cases.
Ruby Familiarity: Understand Ruby/Rails code that generates core transactional data to support debugging and collaboration with product engineering.
Quality Assurance: Serve as the ultimate gatekeeper for data accuracy, ensuring correctness before data reaches the analytics team.
Tool Maintenance: Keep DBT, Airflow, and Superset up to date, manage configurations, and address bugs or performance issues.
Technical Support: Act as the go-to expert for data engineering and analytics teams, assisting with complex queries, performance optimization, and infrastructure challenges.
Proven Leadership: 5+ years of experience in a formal or informal leadership role (Tech Lead, Senior, or Manager) on a data team, with a strong commitment to mentorship.
Education: Degree in Computer Science, Data Science, or a related field.
Expert-Level Technical Skills: Deep, hands-on expertise with our core stack:
DBT: Extensive experience building, maintaining, and reviewing complex DBT projects.
Airflow: Strong experience designing, scheduling, and monitoring reliable data pipelines.
SQL / PostgreSQL: Expert-level SQL skills, including performance tuning and database maintenance.
BI Tools: Experience with Superset, Power BI, Looker, or Tableau (Superset preferred).
Python: Strong proficiency, particularly for data pipelines and infrastructure work.
Ruby: Basic working knowledge to understand the broader application infrastructure.
Fanatical About Data Quality: Demonstrated experience owning data accuracy and validation end-to-end.
Agile Experience: Comfortable running agile sprints, managing a Kanban board, and prioritizing team work effectively.
Excellent Communicator: Able to explain complex technical concepts, set priorities, and manage stakeholder expectations.
Proactive & High-Ownership: Consistently identifies opportunities to improve systems, processes, and team effectiveness without waiting to be asked..
If this sounds like the right role for you, please apply today and let us know why. We look forward to hearing from you!