Big data technology is widely adopted across many disciplines. In order to build sustainable big data application systems and facilitate its rapid development and delivery of expected values with minimum efforts, innovative software engineering methodology and an integrated development and management platform for big data applications are in dire needs. Big data is complex, volatile, lack of correlation and value scarce by nature, which makes it difficult to form standardized and systematic technological solutions to meet the diversified requirements for life cycle management of big data in different application domain. Software engineering in big data era has to address two major challenges:data life cycle management with integrated development environment and software life cycle management using run-time behavior analysis tool. This paper proposes a domain requirements driven approach for big data application systems development and run-time support platform, covering the entire big data life-cycle, including dada collection, storage, computation, analysis, visualization, as well as the software systems life cycle. This platform forms a self-managing, self-adaptive, self-optimizing solution. The proposed techniques are applied in specific application domains such as industry 4.0 and meteorological engineering to provide an illustration and validation of the new platform.