VP/AVP, Data Engineer, UOB Asset Management - Business Technology

Job Responsibilities • Develop and maintain infrastructure for enterprise data platforms and machine learning. • Collaborate with business stakeholders to gather requirements and translate them into effective data visualizations and reporting solutions. • Design, build, and maintain scalable and interactive dashboards using BI tools such as Power BI, Tableau, or Looker. • Implement and manage data governance frameworks, including data cataloging, lineage, quality, and access controls using cloud-native tools (e.g., AWS Glue, Azure Purview, Google Cloud Data Catalog). • 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.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. • Employing 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 5 years of experience in data engineering, business intelligence, machine learning engineering, or a related role in a production environment. • Familiarity with data governance frameworks (e.g., DAMA-DMBOK) and regulatory compliance (e.g., GDPR, CCPA). • Hands-on experience in Python and SQL. Experience with other programming languages (e.g., Java, Scala, C++) is a plus. • Experience in best practices such as 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.