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.
