Asset Management Data Engineer / Data Platform Engineer (Azure / SQL / ELT / UAT / BlackRock / MSCI)
Summary
Build and optimize scalable ETL/ELT pipelines on Azure and Microsoft Fabric to process investment, portfolio, and risk data for an asset management client.
Maltem Apac is looking for Data Engineer for one of our investment management client.
Role: Senior Data Engineer
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, portfolio, and risk analytics.
- Integrate data from multiple internal and external sources using APIs, SFTP, and file-based interfaces, 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.
Requirements
- 7+ years of hands-on experience as a Senior Data Engineer.
- Strong expertise in Microsoft Azure and Microsoft Fabric (Data Factory, Lakehouse, OneLake, Data Warehouse).
- MUST HAVE ASSET MANAGEMENT experience with financial data domains, high-scale data pipelines.
- Strong experience building ETL/ELT pipelines, data lakes, and enterprise data warehouses.
- Proficiency in SQL and Python.
- Experience in Investment Management, Asset Management, Wealth Management, or Portfolio Management domains.
- 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 highly desirable.
- 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.