Data Engineer, VP | Singapore, SG | Hybrid

Morgan McKinley; Singapore; Hybrid; SGD 120,000 - 160,000; Full time

Job summary

A leading regional asset management firm is seeking a Data Engineer, VP to enhance its cloud-based data platforms. This role involves designing and optimizing data infrastructure for analytics and machine learning, ensuring compliance with financial regulations. The ideal candidate will have over 10 years of experience in data engineering, proficiency in Python and SQL, and familiarity with cloud technologies. Join a collaborative team to drive innovation in investment decision-making.

Benefits

Performance Bonus

Qualifications

• 10+ years in data engineering or architecture.
• Experience with cloud platforms, especially GCP.
• Strong communication skills.

Responsibilities

• Design and manage scalable cloud-based data platforms.
• Ensure platform reliability and compliance with regulations.
• Develop efficient data pipelines using modern ETL/ELT frameworks.

Skills

Python

SQL

Communication

Tools

BigQuery

Kafka

CI/CD

Git

Job description

Data Engineer, VP

Morgan McKinley Singapore Apply now Posted 1 day ago Hybrid Job Permanent Performance Bonus

Data Engineer, VP

Morgan McKinley Singapore Apply now

A leading regional asset management firm backed by a major financial institution, this organization manages a diverse portfolio across Asia. The firm is actively scaling its data capabilities to drive innovation and decision-making across its investment platforms.

Overview

We are seeking an experienced Data Engineer or Data Architect to drive the design, development, and optimization of cloud-based data platforms that support enterprise analytics and machine learning in a regulated financial environment. You will play a pivotal role in shaping the data infrastructure strategy for a regional asset manager, enabling data-driven decision making across investment and business functions.

Key Responsibilities

• Design, build, and manage scalable cloud-based data platforms to support enterprise-wide ingestion, storage, and processing of structured and unstructured data.
• Ensure platform reliability, scalability, and security in alignment with financial regulatory standards.
• Evaluate and integrate modern data technologies (e.g., real-time processing, event streaming) to continuously evolve the platform.
• Develop and maintain efficient batch and real-time data pipelines using modern ETL/ELT frameworks.
• Ensure data integrity and quality through validation, transformation, and reconciliation processes.
• Collaborate with analytics and machine learning teams to deliver reliable data for model training, reporting, and insights.

Governance, Security & Documentation

• Enforce data governance, access controls, encryption, and masking practices in accordance with MAS and internal policies.
• Maintain an up-to-date data catalogue and lineage tracking across systems.
• Champion engineering best practices including DevOps, DataOps, and MLOps.

Key Requirements

• 10+ years of experience in data engineering, data architecture, or machine learning engineering in production environments.
• Proficient in Python and SQL; familiarity with Java, Scala, or C++ is a plus.
• Hands-on experience with cloud platforms (GCP preferred, AWS acceptable), especially BigQuery, Kafka, and related services.
• Strong understanding of CI/CD, version control (Git), and automated testing frameworks.
• Background in financial services or asset management is advantageous but not required.
• Strong communication skills with the ability to work both independently and within a collaborative team.

If you're interested in the above role, click on the 'apply' function now! Alternatively, you can contact Mon Fei at for a confidential discussion. Only shortlisted candidates will be notified.

Morgan McKinley Pte Ltd | EA Licence No: 11C5502 | EA Registration No. R1877534

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