Beyond this technical ownership, the role mentors and coaches less experienced engineers, partners closely with data science, analytics, and application engineering teams to align on pipeline design, and communicates pipeline decisions and data quality tradeoffs clearly to both technical and non-technical partners. Additionally, they build, test, and maintain data pipeline architectures, create data validation methods and data quality tooling, and develop, host, and maintain data products to improve reliability and confidence through monitoring, testing, and validation.