Data Engineer - Investment Risk & Portfolio Analytics

Empower Partners Singapore; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

100% in-office

Job summary

Empower Partners Singapore is hiring a Data Engineer to build and own the investment risk and portfolio analytics infrastructure in a newly created role with strong ownership. You will lead the design of data models, data warehouses and end-to-end data pipelines while coordinating with investment teams, data vendors and external partners.

The role requires 5–8 years in financial services data engineering, a degree in a related field, and the ability to communicate complex technical details to

Qualifications

• 5–8 years of data engineering experience in financial services.
• Strong hands-on experience in data modelling, data warehouses and ETL pipelines.
• Ability to explain technical matters clearly to business stakeholders.

Responsibilities

• Own the technical delivery and ongoing operation of an enterprise risk and portfolio analytics platform.
• Design investment data models, data warehouses and platform workflows.
• Build automated data pipelines across internal systems, custodians and data vendors.
• Establish data quality, reconciliation and monitoring controls.
• Support implementation, UAT, access management, parallel runs and go-live.
• Act as the technical bridge between business users and external vendors.
• Oversee production monitoring and platform operations, driving automation.

Skills

Data modelling

ETL pipelines

Data warehouses

Communication

Vendor management

Education

Degree in Computer Science / Engineering / Finance

Job description

Empower Partners Singapore is hiring a Data Engineer to build and own the investment risk and portfolio analytics infrastructure in a newly created role with strong ownership. You will lead the design of data models, data warehouses and end-to-end data pipelines while coordinating with investment teams, data vendors and external partners.

The role requires 5–8 years in financial services data engineering, a degree in a related field, and the ability to communicate complex technical details to