Azure Data Platform Engineer - Asset Management ETL/ELT

Maltem Asia-Pacific; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Maltem Apac seeks a Senior Data Engineer to design, build and optimize scalable ETL/ELT pipelines on Microsoft Azure and Fabric. You will develop Lakehouse, data warehouses, and data models for investment analytics across portfolios and risk data.

Ideal candidates have 7+ years in data engineering, strong SQL and Python skills, and hands‑on asset/wealth management domain experience. You will collaborate with cross‑functional teams and improve governance and performance.

Qualifications

• 7+ years of hands‑on experience as a Senior Data Engineer.
• Expertise in Microsoft Azure and Microsoft Fabric (Data Factory, Lakehouse, OneLake, Data Warehouse).
• Asset management experience with financial data domains and high‑scale pipelines.
• Strong SQL and Python skills.
• Experience in Investment/Asset/Wealth/Portfolio management domains.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines using Microsoft Azure and Microsoft Fabric.
• Develop and maintain Lakehouse, Data Warehouse, and data models for investment analytics.
• Integrate data from APIs, SFTP, and file-based interfaces with governance and validation.
• Build and support pipelines for holdings, positions, pricing, NAV, benchmarks, and analytics datasets.
• Optimize SQL queries, data processing, and platform performance.
• Collaborate with business and technology teams to deliver scalable data engineering solutions.
• Support testing, deployment, production monitoring, troubleshooting, and continuous improvements.

Skills

Microsoft Azure

Microsoft Fabric

SQL

Python

ETL/ELT pipelines

Data Modeling

REST APIs

SFTP

Data governance

Tools

Microsoft Azure Data Factory

Microsoft Fabric

SQL Server

Job description

Maltem Apac seeks a Senior Data Engineer to design, build and optimize scalable ETL/ELT pipelines on Microsoft Azure and Fabric. You will develop Lakehouse, data warehouses, and data models for investment analytics across portfolios and risk data.

Ideal candidates have 7+ years in data engineering, strong SQL and Python skills, and hands‑on asset/wealth management domain experience. You will collaborate with cross‑functional teams and improve governance and performance.