Data Engineer for Dashboards

We are Educate!, a non-profit social enterprise that prepares young people across East Africa with the skills to succeed in today's economy. We are becoming a data and AI native organization, and our Performance Metrics team turns field and program data into dashboards that teams actually use to run their work. We are looking for a hands-on data engineer to help us build out the dashboards and data pipelines for our Tanzania program, Mewaka. Right now we are building the next version of our Mewaka dashboards (a self-built setup, moving away from our old tools) along with the Term 2 dashboards, and we need someone who can own the data engineering behind them. That means shaping the pipelines that bring our data into BigQuery, modeling it cleanly in dbt, and turning it into dashboards that are accurate, timely, and genuinely useful to our Tanzania team and leadership. You will work closely with our Performance Metrics analysts and our central data engineering lead, so you do not have to figure everything out alone, but we do want someone who can take ownership and move quickly. Good data quality matters a lot to us: we care that our numbers are accurate, complete, timely, consistent, and traceable, because real program decisions get made off these dashboards. You will be a strong fit if you are fluent in SQL, have built with dbt before (models, tests, documentation), and are comfortable in a cloud warehouse, ideally BigQuery. Experience building dashboards, whether in Looker Studio or a self-built BI setup, is important, and any Python or experience supporting monitoring and evaluation work is a welcome bonus. Because our team is spread across several countries, we work asynchronously and value people who communicate clearly and keep things moving without a lot of hand-holding. If this sounds like you, tell us briefly about a dbt project you built on BigQuery: what the problem was, how you structured your models, and how you kept the data clean.