Data-driven systems need trust. This course teaches the principles of data governance, ethical AI, compliance, and responsible data stewardship in engineering projects involving large-scale datasets. This course provides a comprehensive exploration of responsible data practices in modern data-driven systems. It focuses on instilling trust through ethical AI development, robust data governance, and strict adherence to global compliance standards such as GDPR, HIPAA, and SOC2. Learners will gain practical skills in implementing data access controls, ensuring transparency, managing data ownership and consent, and using tools for auditing and data lineage. Emphasis is also placed on understanding and mitigating algorithmic bias to promote fairness in AI systems. By the end of the course, participants will be equipped to integrate ethical, legal, and technical safeguards into large-scale engineering projects involving sensitive data.