Data Engineer

Singapore, Singapore

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Design, build, and maintain efficient, scalable, and reliable ETL/ELT data pipelines across banking systems.
Write and optimize complex SQL queries for large-scale transactional and analytical data processing.
Work with Spark (batch/streaming) and Hive for data ingestion, transformation, and aggregation.
Collaborate with business analysts, data scientists, and stakeholders to understand data needs and deliver solutions.
Ensure data quality, governance, and compliance with banking regulations.
Monitor, troubleshoot, and enhance data workflows to meet performance and availability standards.
Support migration and integration of data from traditional databases into modern big data platforms.

Requirements

5-8 years of experience as a Data Engineer or similar role in the banking/financial services domain.
Strong expertise in SQL (query tuning, stored procedures, performance optimization).
Hands-on experience with Spark (medium proficiency) and Hive (medium proficiency).
Good understanding of data warehousing concepts, ETL workflows, and data modeling.
Familiarity with banking data domains such as payments, loans, compliance, or customer data is a plus.
Experience with Unix/Linux scripting and version control (Git).
Ability to work in Agile/DevOps environments and collaborate with cross-functional teams.

Loans

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