Staff Data Engineer

Successful candidates will be responsible for:

• Solving our unique data‑lake challenges: transforming and seamlessly normalizing highly varied partner datasets (such as donation data);

• Design robust batch‑processing pipelines capable of extracting and loading massive datasets from a variety of internal, external, and public sources;

• Developing processes for data mining, data modeling, and data production;

• Leveraging modern technology knowledge to champion evolving industry trends, updated design patterns, and engineering excellence across the team;

• Autonomously scope, design, and execute complex data projects from day one, turning ambiguous requirements into clear, decisive technical plans;

• Developing robust testing and monitoring systems for scheduled processes;

• Collaborating with cross‑functional teams to support their data infrastructure needs; and

• Joining each and every one of your colleagues in creating an inclusive workspace.

Must‑have Qualifications:

• 5 years of professional software engineering experience;

• Eagerness to mentor and technically guide engineering teams;

• Experience guiding technical decision making;

• Extensive, hands‑on experience building distributed data pipelines using Apache Spark;

• Knowledge of how to build and optimize data pipelines, architectures and data sets with the ability to drive additional learning for knowledge gaps;

• Experience managing data warehouses and/or data lakes;

• Intellectual curiosity to innovate on ways to solve data management issues; and

• Passion, energy, and excitement for progressive and philanthropic causes.

Nice‑to‑have Qualifications:

• Experience training or using machine learning models;

• Experience in key DevOps/Infrastructure technologies such as AWS, GitHub Actions, Terraform, and Docker;

• An eagerness to lead and take ownership of complex projects;

• Experience mentoring or managing engineers; and

• Experience working with cross‑functional teams in a dynamic environment.