Nowadays Linux Containers 1 which have operating system level virtualization, are very popular over virtual machines (VMs) which have hypervisor or kernel level virtualization in high performance computing (HPC) due to reasons, such as high portability, high performance, efficiency and high security . Hence, LXCs can make an efficient and secure big data analytic framework with the help of secure, efficient, easily scalable, and highly available databases. A concern for security on high performance computing clusters is high for the transdisciplinary Texas Tech University (TTU) EXPOSOME Project. This project mainly focuses on sensitive healthcare data which is operating in the Quanah Linux cluster in the High Performance Computing Center of Texas Tech University. Data privacy in this project is in 4 areas: the database, the network infrastructure, web applications, and physical security, in line with the Health Insurance Portability and Accountability Act (HIPAA). The study in this paper investigates how to assure the TTU EXPOSOME Project data security by proposing a secure data analytic framework with the Singularity Linux container and the MongoDB NoSQL database, commonly available at TTU. First, the paper investigates what are the advantages of LXCs over VMs with security and performance perspectives. Then, it focuses on four main HIPAA required areas in data security, such as authentication, authorization, encryption, and auditing, in order to make sure system security is assured to handle healthcare data. Finally it shows how the TTU EXPOSOME Project strengthens security in the aforementioned four areas using MongoDB and Singularity, such that system security is approaching compliance with HIPAA.