Can data engineering be feminist? Absolutely. As data engineers and Python developers, the decisions we make about what data to collect, how we transform it, and who gets access carry ethical weight. This talk explores how we can apply feminist principles like transparency, consent, and equity to build more ethical data pipelines. Through real-world examples of harm caused by opaque and biased data systems, we’ll examine how even routine ETL work can reinforce injustice. We’ll then outline practical approaches for designing pipelines that center care and accountability covering techniques like schema minimization, anonymization in Python, and documenting data provenance. Attendees will leave with a deeper understanding of how to challenge extractive data practices and use their technical skills to push back against surveillance capitalism and systemic bias.