Data Engineer, VP
Singapore Full-time
About the Company 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 Enterprise Data Platform & Architecture 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. Data Engineering & Pipelines 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!
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 regul
About the Company 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 Enterprise Data Platform & Architecture 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. Data Engineering & Pipelines 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 Chow Mon Fei EA Licence No: 11C5502 EAP Registration No: R1877534
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