Junior Data Engineer
We are a Singapore FinTech company spun off from the National University of Singapore in 2017. We are a cohesive team comprised of 18 domain experts and talents.
We specialize in Deep Credit Analytical Technologies that have been developed from more than 10 years’ world-leading research achievements. Our technologies have been highly recognized by the global financial industry, e.g., the International Monetary Fund (IMF), the World Bank, and prominent financial institutions.
We productize and commercialize our proprietary, new-generation technologies to help financial institutions on Intelligent Transformation in credit risk and investment management. We provide a suite of analytical data & tools, and enterprise solutions to serve Banks, Insurance Companies, Asset Managers in the US, China, and Asia. We recently launched our wholly-owned subsidiary in Shanghai to facilitate our business development in China.
Role and Responsibilities
We are looking for a savvy Data Engineer to join our growing team of credit data & analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The Data Engineer will support our credit analysts, analytics engineers, and software developers on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. He/she must be self-directed and comfortable supporting the data needs of products and projects. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
Your role responsibilities include but are not limited to:
- Design and maintain optimal data architecture including database and data warehouse and data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Create data tools for credit analysts and analytics engineers that assist them in building and optimizing our product into an innovative industry leader.
- A candidate with 1-3 years’ hands-on working experience in a Data Engineer role and a bachelor’s or master’s degree in computer science, statistics, informatics, information systems, or another quantitative field.
- Deep understanding of database, including database architectures, database design, database tuning
- Experience with one SQL-based technology e.g. MySQL, Microsoft SQL Server, and Oracle SQL
- Experience with one programming language e.g. Python, Java and Golang
- Experience with Linux and Shell Script
- Experience with data warehouse and ETL technologies is a plus, e.g. Kimball Dimension Model
- Experience with one of NoSQL technologies is a plus, e.g. MongoDB, Redis and ElasticSearch
- Experience with big data tools is a plus: Hadoop-based technologies (e.g. MapReduce, HDFS, Hive, and Pig)
- Experience with one of the cloud computing platforms is a plus: AWS, AliCloud, etc
- Having some knowledge of machine learning, deep learning is a plus
- You will obtain a deep knowledge of world-leading credit analytical technologies.
- You will gain exposure to a full cycle of financial risk product development and operation.
- You will receive competitive compensation.
- You will be awarded stock options or other incentive compensation if your performance is recognized.