The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred installation of ubiquitous sensors in complex engineered systems. However, ensuring reliable data quality remains a difficult challenge. This can be addressed by exploitation of redundancy among sensor signals, e.g. to improve the precision of measured variables, to detect the presence of gross errors, and identify faulty sensors. Despite these automated methods, the cost of sensor ownership, maintenance efforts in particular, can be cost-prohibitive. To maximize the ability to assess and control data quality while also maximizing the information content of the collected sensor signals and minimizing the cost of onwership, the selection and placement of sensors must be executed carefully. To solve this, we develop a method to solve the multi-objective sensor placement problem in typical wastewater treatment plants. This method is deterministic and enables computation of all Pareto-optimal sensor layouts with conventional computational resources.