Responsibilities:· Design and build the microservice app to migrate existing internal and external dashboard from tableau to Plotly/dash, Align the UI/UX experience close to the existing tableau reports· Capable of reading and writing SQL statements to aggregate values from SQL Server· Providing constructive input into architectural decisions for new feature· Able to work in agile teams by collaborating with other engineers using Jira software and GitHub version control.Achievements:· Zero to one design and build the customized like MVC architecture dash app that can support at least 80 dynamic dashboards operating at the same time. Developed Internal and external dashboard templates and encapsulation it for rapidly building new dashboard with different datasets.· Dynamically produced real-time customised SQL query based on user filter input to collect aggregate numbers for plotting the chart and KPI calculation.· The architecture includes routeing, logging, caching, database connection, and docker environment services that are suitable for enterprise purposes· Complete all Sprint tasks on schedule and leave ample time for testing to the QA team. Creating a process diagram and writing documentation/comment to aid with knowledge transfer

Responsibilities:• Working in an agile team, developed a data visualization package (Paper-Viz) using Python Matplotlib, pandas, seaborn, NumPy, geopandas packages, which is designed to help to plot professional graph in the research paper with simple code• Designed and built ETL process to transform multiple sources to become the well-structured and clean format for the next step data visualisation and data modeling• Developed complicated data visualisation application and drew professional charts (bubble,scatter,radar and map) by using Excel, Python pandas, and Tableau• Built up a parameter-driven plotting system that can adapt to different plotting schemes based on the user's supplied data • Constructing and implemented a number of usage guides for certain professional plots• Github link: https://github.com/swsamleo/Paper-VizAchievements:• Compared with the traditional plotting methods, paper-Viz’s plotting library can save 80%-90% time for plotting a professional graph• Support users to import various types of files (such as csv, xlsx, text, geojson) and transform them to Pandas data frame for next step plotting• Applying EDA analysis, remove the outlier from the example Chart to make it more attractive to users• Developed good research skills, including the ability to obtain and use information from the matplotlib manual