Data Pipeline Engineer: Build Scalable, Reliable Data Flows

Newport World Resorts; Pasay; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

Newport World Resorts is seeking a data engineer to design, build, and maintain scalable data transformation pipelines that support the enterprise data platform. The role focuses on transforming raw operational data into structured datasets, aligned with enterprise architecture standards, enabling analytics and machine learning workflows.

Collaborate with IT teams responsible for data ingestion and with analytics teams to ensure data availability, quality, and timely delivery.

Qualifications

• Bachelor’s degree in CS/IS/Data Engineering or related field.
• At least 3 years in data engineering, data transformation, or pipeline development.
• Experience with SQL-based transformations and modern data warehouses.

Responsibilities

• Develop and maintain structured data transformation pipelines within the enterprise data platform.
• Transform raw operational data into structured datasets aligned with architecture standards.
• Implement reusable transformation logic to support consistent data processing.
• Optimize transformation processes to improve performance and scalability.
• Maintain structured workflows that support continuous data processing.
• Collaborate with IT, Senior Analytics Engineers, and Data & Analytics teams to ensure data availability and usability.
• Maintain documentation for transformation workflows and governance practices.

Skills

Data pipelines

Data transformation

SQL

Data warehouse

Education

Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, or related discipline

Job description

Newport World Resorts is seeking a data engineer to design, build, and maintain scalable data transformation pipelines that support the enterprise data platform. The role focuses on transforming raw operational data into structured datasets, aligned with enterprise architecture standards, enabling analytics and machine learning workflows.

Collaborate with IT teams responsible for data ingestion and with analytics teams to ensure data availability, quality, and timely delivery.