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VP, Data Engineer, Group Asset Management – Business Technology
Company Overview
A leading bank in Asia, headquartered in Singapore, with a history dating back to 1935. Initially named United Chinese Bank, it was founded by a group of businessmen to serve the merchant community in Singapore amidst the economic uncertainties of the Great Depression. It was later renamed in 1965.
Job Description
As a VP, Data Engineer within the Group Asset Management – Business Technology team, you will be responsible for developing and maintaining the infrastructure underpinning our enterprise data platforms and machine learning capabilities. Your role will involve the full lifecycle of data platform development and management, from design to implementation and ongoing maintenance, ensuring scalability, reliability, and security. You will also be instrumental in building and maintaining robust data pipelines and ensuring data quality.
Job Responsibilities
Develop and maintain infrastructure for enterprise data platforms and machine learning.
Data Platform Development & Management:
Design, develop, and maintain data platforms that support large-scale data ingestion, storage, and processing using cloud-based data infrastructure.
Implement and manage data warehousing and centralized data solutions tailored for asset management.
Ensure data platform scalability, reliability, and security in accordance with financial regulators and policies.
Evaluate and integrate new data technologies and tools to enhance data platform capabilities.
Data Pipeline Development:
Build and maintain robust and efficient data pipelines for data ingestion, processing, and transformation.
Develop and implement data quality checks and validation processes to ensure data accuracy, timeliness, and consistency.
Utilize ETL/ELT tools and techniques to transform and load data into target systems.
Implement and enforce data security best practices including access control, encryption, data masking to identify and safeguard sensitive data in accordance with respective regulatory requirements and internal policies.
Maintain data catalogue for all data assets, and metadata lineage.
Employ exceptional problem-solving skills, with the ability to see and solve issues before they snowball into problems.
Learn and share knowledge and experience in a multi-disciplinary team.
Job Requirements
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
At least 10 years of experience in data modelling, engineering, machine learning engineering, or a related role in a production environment.
Highly proficient in Python and SQL. Experience with other programming languages (e.g., Java, Scala, C++) is a plus.
Experience in best practices such as DevOps, DataOps and MLOps
Experience with big data technologies and cloud platforms such as BigQuery, Kafka, GCP, AWS and their data engineering and machine learning products and services.
Strong understanding of software development best practices, including version control (Git), testing, and CI/CD.
Excellent communication and organizational skills, and the ability to stay focused on completing tasks and meeting goals within a busy workspace.
Skilled at working in tandem with a team of engineers, or alone as required.
Strong troubleshooting and analytical skills.
Cloud and data certifications are a plus.
Disclaimer
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