Senior Data Engineer - Monee

Monee SG Private Limited; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Monee is a leading digital payments and financial services provider in Southeast Asia, seeking a data engineer to build and optimize batch and real-time feature pipelines and data marts. You will work on data quality, modeling, and ETL to support data requirements across regulatory and business teams.

Join a fast-growing environment where you will tackle high-throughput data challenges, collaborate with policy, risk, and product teams, and contribute to scalable analytics platforms for Southeast

Qualifications

• 3+ years of full-time data engineering or big data development experience.
• Strong SQL and Python/Scala/Java skills.
• Hands-on Spark/Flink for batch or streaming processing.
• Solid understanding of data warehousing, dimensional modeling, and Data Mart development.
• Familiarity with Kafka, Hive, and Airflow.
• Experience with Feature Engineering, Feature Stores, or data/feature platforms.

Responsibilities

• Develop, optimize, and maintain batch and real-time feature pipelines using Spark/Flink.
• Design, build, and maintain business Data Marts, including data modeling, ETL development, and performance optimization.
• Ensure data quality, accuracy, and pipeline reliability, continuously improving data processing efficiency.
• Collaborate with DS, policy, risk and business teams to support feature engineering and data requirements.

Skills

SQL

Python

Scala

Java

Spark

Flink

Data Warehousing

Airflow

Kafka

Data Modeling

Tools

Kafka

Hive

Airflow

Job description

About Monee

Monee is a leading digital payments and financial services provider in Southeast Asia, with a growing presence in Latin America. Its mission is to better the lives of individuals and businesses in the region with financial services through technology.

Monee delivers a comprehensive range of digital financial products and services, including mobile wallets, payment processing, credit, banking, and insurtech. By leveraging technology and strategic partnerships, Monee aims to drive greater digital financial inclusion, convenience, and accessibility for individuals and small businesses across Southeast Asia and Latin America.

Monee is part of Sea Limited, a global technology company.

Monee is a leading digital payments and financial services provider in Southeast Asia, with a growing presence in Latin America. Monee delivers a comprehensive range of digital financial products and services, including mobile wallets, payment processing, credit, banking, and insurtech.

At Monee, engineers work directly on our core business, product innovation, and infrastructure. We help turn proven capabilities into platforms that can scale, while also building new markets, products, and financial services from the ground up.

Our financial business operates across multiple markets at scale, bringing complex, real-world engineering challenges from high-throughput systems and safeguarding funds to global architecture and regulatory compliance. It also creates ample room for engineering innovation in the age of AI. We’re looking for talented engineers with strong fundamentals, a passion for learning, and a curiosity about solving complex problems.

• Develop, optimize, and maintain batch and real-time feature pipelines using Spark/Flink.
• Design, build, and maintain business Data Marts, including data modeling, ETL development, and performance optimization.
• Ensure data quality, accuracy, and pipeline reliability, continuously improving data processing efficiency.
• Collaborate with DS, policy, risk and business teams to support feature engineering and data requirements.

• At least 3 years of full time experience in data engineering or big data development, with strong SQL and Python/Scala/Java skills.
• Hands-on experience with Spark/Flink for batch or stream processing.
• Solid understanding of data warehousing, dimensional modeling, and Data Mart development.
• Familiarity with big data technologies such as Kafka, Hive, and Airflow.
• Experience with Feature Engineering, Feature Stores, or data/feature platforms.