Asset Management Data Engineer / Data Platform Engineer (Azure / SQL / ELT / UAT / BlackRock / MSCI)
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maltem asia pte. ltd. Asset Management Data Engineer / Data Platform Engineer (Azure / SQL / ELT / UAT / BlackRock / MSCI)
Maltem Asia is seeking a
Data Engineer
for our Asset Management client. Responsibilities: Design, build, and optimize scalable
ETL/ELT pipelines
using
Microsoft Azure
&
Microsoft Fabric . Develop and maintain
Lakehouse, Data Warehouse, and data models
for investment, portfolio, and risk analytics. Integrate data from multiple internal and external sources using
APIs, SFTP, and file-based SQLinterfaces , ensuring data quality, validation, reconciliation, and governance. Build and support data pipelines for portfolio holdings, positions, security master, 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 platform improvements. Skillset Requirements: MUST HAVE
strong exposure and hands-on experience in managing data within the
Asset Management
or Financial Markets
domain. Strong hands-on experience using SQL as a core tool
for complex window functions (PARTITION BY), stored procedures, indexing strategies, recursive queries, and query plan analysis. 5 to 8 years
as a
Data Engineer . Strong expertise in
Microsoft Azure
and
Microsoft Fabric
(Data Factory, Lakehouse, OneLake, Data Warehouse). Strong experience using
Python. Strong experience building
ETL/ELT pipelines , data lakes, and enterprise data warehouses Good understanding of investment data, including
portfolio holdings, positions, security master, pricing, NAV, benchmarks, and risk analytics . Knowledge of enterprise investment platforms such as
BlackRock Aladdin, MSCI BarraOne, Bloomberg, FactSet, SimCorp, Charles River IMS , or equivalent is a plus. Experience with
REST APIs, SFTP, and file-based data integrations . Strong knowledge of data modeling, data quality, governance, and cloud-based data platforms. Excellent analytical, stakeholder management, and communication skills.
Data Engineer
for our Asset Management client. Responsibilities: Design, build, and optimize scalable
ETL/ELT pipelines
using
Microsoft Azure
&
Microsoft Fabric . Develop and maintain
Lakehouse, Data Warehouse, and data models
for investment, portfolio, and risk analytics. Integrate data from multiple internal and external sources using
APIs, SFTP, and file-based SQLinterfaces , ensuring data quality, validation, reconciliation, and governance. Build and support data pipelines for portfolio holdings, positions, security master, 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 platform improvements. Skillset Requirements: MUST HAVE
strong exposure and hands-on experience in managing data within the
Asset Management
or Financial Markets
domain. Strong hands-on experience using SQL as a core tool
for complex window functions (PARTITION BY), stored procedures, indexing strategies, recursive queries, and query plan analysis. 5 to 8 years
as a
Data Engineer . Strong expertise in
Microsoft Azure
and
Microsoft Fabric
(Data Factory, Lakehouse, OneLake, Data Warehouse). Strong experience using
Python. Strong experience building
ETL/ELT pipelines , data lakes, and enterprise data warehouses Good understanding of investment data, including
portfolio holdings, positions, security master, pricing, NAV, benchmarks, and risk analytics . Knowledge of enterprise investment platforms such as
BlackRock Aladdin, MSCI BarraOne, Bloomberg, FactSet, SimCorp, Charles River IMS , or equivalent is a plus. Experience with
REST APIs, SFTP, and file-based data integrations . Strong knowledge of data modeling, data quality, governance, and cloud-based data platforms. Excellent analytical, stakeholder management, and communication skills.