When it comes to data engineering policies and procedures related to handling data requests from people, there are several important considerations to ensure data privacy, security, and compliance. Here are some key aspects to consider:

1. Data Governance: Establish a robust data governance framework that outlines the roles, responsibilities, and processes for managing data requests. This framework should define the data ownership, access controls, and data classification standards.
2. Data Request Process: Implement a standardized process for handling data requests. This process should include clear guidelines for submitting requests, specifying the required information, and defining the expected turnaround time.
3. Data Access Controls: Define access controls to determine who can request data and who can access specific datasets. Implement user authentication mechanisms, role-based access controls (RBAC), and data access logging to monitor and track data access activities.
4. Data Privacy and Consent: Ensure compliance with applicable data privacy laws (e.g., GDPR, CCPA) by obtaining proper consent from data subjects before processing their data. Implement mechanisms to handle data anonymization, pseudonymization, and data masking techniques to protect individual privacy.
5. Data Security: Implement robust security measures to protect data from unauthorized access, modification, or disclosure. This includes encryption of data in transit and at rest, network and system security measures, regular security audits, and vulnerability assessments.
6. Data Retention and Deletion: Define policies for data retention and deletion to ensure compliance with legal and regulatory requirements. Establish guidelines for how long data should be retained and implement procedures for secure data disposal.
7. Documentation and Auditing: Maintain detailed documentation of data requests, including the purpose, scope, and outcome of each request. Implement auditing mechanisms to track data access, changes, and activities for accountability and compliance purposes.
8. Data Quality and Integrity: Ensure data quality and integrity by implementing data validation checks, data cleansing processes, and data quality monitoring mechanisms. Regularly review and update data engineering procedures to improve data accuracy and reliability.
9. Training and Awareness: Provide training and awareness programs for employees involved in the data request process to ensure they understand the policies and procedures. This includes educating employees about data privacy, security best practices, and their roles in data protection.
10. Regular Review and Improvement: Continuously review and improve data engineering policies and procedures to adapt to evolving data privacy regulations, technological advancements, and organizational needs. Regularly assess the effectiveness of existing processes and make necessary updates.

Remember that these policies and procedures should align with your organization's overall data strategy and comply with relevant legal and regulatory requirements. It is advisable to consult with legal and compliance teams to ensure adherence to specific industry standards and guidelines.