Data Engineer

About the Role

The Kuala Lumpur office is the technology powerhouse of MoneyLion. We pride ourselves on innovative initiatives and thrive in a fast paced and challenging environment. Join our multicultural team of visionaries and industry rebels in disrupting the traditional finance industry!

MoneyLion is building a world class data ecosystem that will dramatically improve the ability of internal data users and analysts to create products and experiences that captivate our customers. As the Data Engineer, you will participate in technical and architectural planning as well as contributing as a developer while interacting with data scientists, software engineers, and analysts as we build and scale the world's most rewarding program for financial wellness.

Key Responsibilities

• Assist with reviewing and interpreting business and technical requirements with a focus on data objectives of the product
• Identify requirements and develop data delivery solutions
• Implement company policies on data access and data distribution
• Support members of various teams to determine database structural requirements by analyzing their applications and client operations
• Collaborate with highly talented engineers while striving to help them build their skills and achieve their career goals
• Support data flow and ETL processes from end to end for projects and initiatives including troubleshooting of data issues, integrity checks, data model design, querying of data, and performance resulting from data issues
• Assist in training over the data systems used by the company for the employees. Specifically, training programs for new hires on various reports and models available in the data visualization tools that are used
• Analyze large data sets, some of them messy, to answer and solve real-world business problems while charting paths towards data cleanup and preventing data from becoming messy

About You

• Familiarity with financial and banking products
• Demonstrated skills in good software engineering practices
• Building and shipping large-scale engineering products and/or infrastructure
• Scalable data architecture, fault-tolerant ETL, and monitoring data quality in the cloud (We use AWS)
• Collaborating with a diverse set of engineers, data scientists and product managers
• Deep expertise in data engineering and data processing at scale. Requires a focus on the development of pipelines for the creation of data lakes to enable exploration as well as machine learning model training, deployment and scoring at massive scale.
• Familiarity with data science techniques and frameworks
• NoSQL, Relational databases and Presto (We use MongoDB, MySQL, PostgreSQL, ElasticSearch)
• The AWS stack combined with technologies such as Java, Python, Spark, and Kafka
• Familiarity with Apache Airflow or equivalent workflow management tools

What's Next...

After you submit your application, you can expect the following steps in the recruitment process: