Data Engineer (Credit) - Sea Labs

PT Sea Group; Jakarta Pusat; On-site; IDR 167,400,000 - 334,800,000; Full time

Job summary

Monee is seeking engineers to work on core data platforms, scaling infrastructure and building new markets and products. You will develop batch and real-time feature pipelines with Spark/Flink, craft Data Marts, and optimize ETL processes to ensure data quality and reliability across regulated environments.

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

Qualifications

• 3+ years of experience in data engineering or big data development.
• Strong SQL and Python/Scala/Java skills.
• Experience with Spark/Flink for batch and stream processing.
• Solid understanding of data warehousing and Data Mart development.
• Familiarity with Kafka, Hive, and Airflow.

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 modeling

ETL development

Data warehousing

Tools

Kafka

Hive

Airflow

Job description

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.
• 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.