Data Engineer (Data Analyst, Python, SQL)

About FinhayFounded in 2017, Finhay is currently one of the most popular individual-investment digital platform in Vietnam with more than 2.7 million users. Concurrently, Finhay is the owner of a securities company (license number 50/UBCK-GPHDKD issued by the State Securities Commission on December 29, 2006).Finhay has been certified as a Science and Technology Enterprise by Hanoi Department of Science and Technology. Moreover, Finhay entered the Top 100 Fintech of the World in 2019, according to KPMG. We have always strived to bring financial investment solutions that are simple and easily accessible through the application of technology. After 5 years of operation, Finhay now owns an "ecosystem" with diverse services which allows users to spend, accumulate, invest and allocate portfolio effectively with products such as securities, gold, fund certificates,…etc. By starting with just a small amount of capital, users can build up solid assets for the future.If you are interested in the dynamic fintech field, love conquering exciting challenges in building a comprehensive financial platform & solution, creating beautiful and valuable products for the community, then Finhay is the place for you.What you will doYour day to day tasks will include, but not be limited to, the following: Working with large datasets and solving difficult analytical problems Conducting end-to-end analyses, including data collection, processing, consolidation and analysis. Designing, building, operationalizing, securing, and monitoring the data processing pipeline and the data warehouse. Creating reliable pipelines after combining data sources. Building prototype analysis pipelines to generate insights Finding trends in data sets and developing an algorithm to make raw data more useful for our product teams Deploying, leveraging, and continually training and improving existing machine learning models Automating manual processes to enhance data delivery. Meeting business objectives in collaboration with data scientists and key stakeholders.