Have a solid understanding of the different components to build up the enterprise data lake.
Use ingestion and egestion tools to create a big data work flow job to ingest and egress diverse data sources from RDBMS, mainframe, NoSQL, HDFS, social media, file systems, search engines, and so on.
Query the big dataset at the runtime; conduct interactive data analytics.
Fit the following jobs: big data platform engineer, data governance, big data security, and big data system support.
It is hard, but you can do it. Plus, we are here to help.
Principal Big Data Engineer
Bin is a principal big data engineer at one of the big financial groups in Toronto. He has also worked with Invesco, RBC, CIBC, CGI, and ING to lead teams in creating enterprise application architecture: Portal, SOA, ESB, EAI, BPM, and ECM/CMS. With over 15 years of work experience in all phases of software development, he is now a big data practitioner in architecting and implementing real-time advanced big data analytics applications and recommendation engines. He has accumulated extensive experience in building an enterprise big data platform with the Hadoop ecosystem and delivering big data solutions. Essentially, Bin is a very skilled architect with cross-industry, cross-functional, and cross-domain know-how.