B2Bnetwork appears to be a technology-focused company operating in the business-to-business (B2B) sector. It specializes in building modern, scalable software solutions, with an emphasis on microservices architecture and contemporary web technologies. The company demonstrates a strong commitment to industry best practices, clean documentation, reusable design systems, and high-quality user interface standards. Its collaborative approach to development and focus on configurable, standardized platforms suggest a mission centered on delivering efficient, adaptable digital solutions for business clients.

· Building distributed and highly parallelized Big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time · Leveraging Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics · Working closely with analysts and business stakeholders to develop analytics models · Continuous delivering on Hadoop and other Big Data Platforms · Automating processes where possible and are repeatable and reliable · Working closely with QA team

· Building distributed and highly parallelized Big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time· Leveraging Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics· Working closely with analysts and business stakeholders to develop analytics models· Continuous delivering on Hadoop and other Big Data Platforms· Automating processes where possible and are repeatable and reliable· Working closely with QA team

Expert Data Engineer

Role focused on designing and building distributed, highly parallelized Big Data pipelines to process massive structured and unstructured data in near real-time. Involves using Spark and Hadoop to transform and enrich data for search, visualization, and advanced analytics, while collaborating with analysts and QA. Emphasis on automation, reliability, and continuous delivery on Big Data platforms.