Successful candidates will be responsible for:
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Solving our unique data‑lake challenges: transforming and seamlessly normalizing highly varied partner datasets (such as donation data);
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Design robust batch‑processing pipelines capable of extracting and loading massive datasets from a variety of internal, external, and public sources;
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Developing processes for data mining, data modeling, and data production;
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Leveraging modern technology knowledge to champion evolving industry trends, updated design patterns, and engineering excellence across the team;
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Autonomously scope, design, and execute complex data projects from day one, turning ambiguous requirements into clear, decisive technical plans;
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Developing robust testing and monitoring systems for scheduled processes;
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Collaborating with cross‑functional teams to support their data infrastructure needs; and
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Joining each and every one of your colleagues in creating an inclusive workspace.
Must‑have Qualifications:
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5 years of professional software engineering experience;
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Eagerness to mentor and technically guide engineering teams;
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Experience guiding technical decision making;
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Extensive, hands‑on experience building distributed data pipelines using Apache Spark;
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Knowledge of how to build and optimize data pipelines, architectures and data sets with the ability to drive additional learning for knowledge gaps;
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Experience managing data warehouses and/or data lakes;
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Intellectual curiosity to innovate on ways to solve data management issues; and
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Passion, energy, and excitement for progressive and philanthropic causes.
Nice‑to‑have Qualifications:
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Experience training or using machine learning models;
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Experience in key DevOps/Infrastructure technologies such as AWS, GitHub Actions, Terraform, and Docker;
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An eagerness to lead and take ownership of complex projects;
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Experience mentoring or managing engineers; and
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Experience working with cross‑functional teams in a dynamic environment.
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