Chief Executive Officer (CEO), who can provide high-level business objectives but lacks the technical expertise to address computational and compliance constraints.

Data Engineer, who can optimize data infrastructure for real-time processing but may not fully grasp the nuances of aligning ML metrics with business goals.

Social Media Manager, who understands user engagement and brand perception but lacks the technical skills to define ML success metrics under given constraints.

Google Cloud Professional Machine Learning Engineer, who can align ML success metrics with business objectives while ensuring the model is scalable, cost-effective, and compliant with data privacy laws.

Both the Google Cloud Professional Machine Learning Engineer and the Data Engineer, as their combined expertise covers both the alignment of ML metrics with business goals and the optimization of data infrastructure for real-time processing.