Cloud Data Engineer for Analytics & AI Platform

PSA Corporation Limited; Santo Niño 1st; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

PSA Corporation Limited is seeking a data engineer to design, build, and maintain scalable data solutions to support analytics, machine learning, and business insights. You will develop robust data pipelines, cloud-based data platforms, analytics solutions, and support AI/ML initiatives while ensuring data quality and governance.

Responsibilities include ETL/ELT development, Azure-based data services, dashboards in Power BI, and collaboration with data scientists to deploy models in production.

Qualifications

• Bachelor's degree in CS/CE or related field.
• 2–3 years in data/ software engineering with cloud/data platforms.
• Strong analytical and collaboration skills; eager to learn.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines across cloud/on-premise environments.
• Develop scalable data models (star/snowflake) for analytics, reporting, and BI.
• Ensure data quality, governance, and security controls.
• Implement and manage cloud-based data solutions on Microsoft Azure (ADF, Data Lake, Azure SQL).
• Support infrastructure configuration and CI/CD, monitoring, and SLA adherence.
• Collaborate with Power BI dashboards and reporting layers.
• Collaborate with Data Scientists to deploy ML models and integrate AI/ML capabilities.

Skills

ETL/ELT development

Python data processing

Azure data platform

Data modeling

Power BI

SQL Server

Data governance

Spark/Databricks

Education

Bachelor’s degree in Computer Science / Computer Engineering

Tools

SSIS

Informatica

Azure Data Factory

Azure SQL

Data Lake Storage

Databricks

Power BI

Azure DevOps

Job description

PSA Corporation Limited is seeking a data engineer to design, build, and maintain scalable data solutions to support analytics, machine learning, and business insights. You will develop robust data pipelines, cloud-based data platforms, analytics solutions, and support AI/ML initiatives while ensuring data quality and governance.

Responsibilities include ETL/ELT development, Azure-based data services, dashboards in Power BI, and collaboration with data scientists to deploy models in production.