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

UOB ASSET MANAGEMENT LTD; Santo Niño 1st; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

UOB Asset Management Ltd in the Philippines is seeking a senior data engineer to design and maintain enterprise data platforms and ML infrastructure. You will collaborate with business stakeholders to deliver insightful dashboards and reports.

You will implement data governance, build scalable data pipelines, and evaluate cloud-based data technologies from AWS, Azure, and Google Cloud to support asset management needs.

Qualifications

• 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, BI, ML engineering, or related role in production.
• Familiarity with data governance frameworks (e.g., DAMA-DMBOK) and regulatory compliance (e.g., GDPR, CCPA).
• Hands-on experience in Python and SQL; other languages are a plus.
• Experience with DataOps and MLOps practices.
• Experience with big data technologies and cloud platforms (BigQuery, Kafka, GCP, AWS) and related services.
• Strong software development practices (version control, testing, CI/CD).
• Excellent communication and organizational skills; able to work independently or in teams.
• Cloud and data certifications are a plus.

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.

Skills

Python

SQL

Data modeling

Data governance

Communication

Team collaboration

Problem solving

Education

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field

Tools

Power BI

Tableau

Looker

BigQuery

Kafka

AWS

Azure Purview

Google Cloud Data Catalog

Git

CI/CD

Job description

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.