Senior Data Systems Architect (ETL, Schema, Validation) “This role requires designing and building end-to-end data pipelines from messy, inconsistent datasets (e.g., municipal or multi-source data). Please do not apply if you have not done this in production.” We’re working on a system to standardize and validate complex municipal datasets (multiple sources, inconsistent formats, real-world messiness). Looking for someone who has hands-on experience building data pipelines and is comfortable working through messy, real-world data. What you’ll help with • Designing how data flows from ingestion → standardization → validation • Defining a clean, consistent schema across different datasets • Building logic to handle inconsistencies, missing fields, and edge cases • Setting up a clear approach for automation vs. human review What we’re looking for • Experience building and deploying data pipelines (ETL/ELT) • Comfortable working with inconsistent or unstructured datasets • Experience with schema mapping / normalization • Familiarity with data validation or QA processes Helpful (not required) • Experience with tools like Airflow, dbt, Spark, or similar • Exposure to multi-source or public-sector data Quick note If you’ve worked on systems like this, feel free to reach out with a short example of something you built—we’d love to hear about it.