Data Engineer (Credit) - Sea Labs

SEA Singapore; Jakarta Pusat; Sur place; IDR 360 000 000 - 600 000 000; Plein temps

Avantages offerts par ce poste

Résumé du poste

Monee is seeking a data engineer to design and optimize both batch and streaming data pipelines using Spark and Flink. You will build and maintain data marts, ensure data quality, and work closely with data science, policy, risk, and business teams to support feature needs.

Ideal candidates have 3+ years in data engineering, strong SQL and Python/Scala/Java skills, and hands-on experience with big data tools like Kafka, Hive, and Airflow.

Qualifications

• 3+ years of experience in data engineering or big data development.
• Strong SQL and Python/Scala/Java skills.
• Hands-on experience with Spark/Flink for batch or streaming.
• Solid understanding of data warehousing and data marts.
• Familiar with Kafka, Hive, and Airflow.
• Preferred: Experience with Feature Engineering or feature platforms.

Responsabilités

• Develop, optimize, and maintain batch and real-time feature pipelines with Spark/Flink.
• Design and maintain business Data Marts, including data modeling and ETL.
• Ensure data quality, accuracy, and pipeline reliability.
• Collaborate with DS, policy, risk and business teams to support data requirements.

Connaissances

SQL

Python

Scala

Java

Data modeling

Airflow

Team collaboration

Outils

Spark

Flink

Kafka

Hive

Airflow

Description du poste

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.

Job Description

• 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.

Requirements

• 3+ years of 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.
• Preferred Qualifications: Experience with Feature Engineering, Feature Stores, or data/feature platforms.