Data Engineer - MoneyLion

The Kuala Lumpur office is the technology powerhouse of MoneyLion, where we measure anything and everything and rely on data to guide our decisions: both long-term strategies and day-to-day operations. Combine that backdrop with an incredible volume and sophistication of data and mix in MoneyLion’s voracious appetite for adopting paradigm-shifting technologies and you have the mission and mandate of the Data Engineering team. As a Data Engineer, you are a technical Individual Contributor (IC) figure within the team that will design, implement and optimize a Snowflake-centric architecture that will leverage many components of the modern data stack. You will be responsible for designing and implementing an analytical environment using in-house and third-party tools, using Python and/or Java to automate data activities and enable efficient processing of data that is growing in both volume and complexity.

Responsibilities

Design, implement and optimize a Snowflake-centric architecture leveraging components of the modern data stack; Design and implement complex data pipelines and data models for analytical consumption; Write scalable and performant SQL queries running over billions of rows of data; Collaborate with data scientists, business analysts, product managers, software engineers and other data engineers to develop, implement and validate deployed data solutions; Build and maintain data pipelines from internal databases and SaaS applications; Implement better solutions for data governance at scale, encompassing lineage, discoverability, and regulatory compliance; Advocate best practices, uphold the highest standards for code maintainability and performance; Lead the team in honing ways of working, coaching and mentoring junior engineers, and managing senior stakeholders from external departments

Requirements

Bachelor's degree in computer science, Data Engineering, or related technical field; 1-4 years of hands-on data engineering experience in large-scale, high-volume environments; Expert-level proficiency in SQL optimization for multi-petabyte datasets and advanced Python programming; Experience with Snowflake architecture, optimization, and cost management at enterprise scale; Demonstrated expertise building Kimball dimensional data warehouses and star schema architectures, or equivalent experience with thoughtful, non-generic projects; Advanced experience with AWS cloud infrastructure and either DBT or SQLMesh for data transformations; Experience in planning day to day tasks, knowing how and what to prioritise and overseeing their execution

Nice to have

Familiarity with AWS is a big plus