Data Engineer

Salary: ₱80,000 – ₱90,000 per month

Required Qualifications

• At least 3 years of professional experience in Data Engineering or a related role.

• Strong proficiency in SQL.

• Strong programming experience with Python.

• Hands-on experience with:

  • AWS S3

  • AWS Redshift

  • AWS IAM — Roles, Users, and Policies

  • AWS Glue

  • AWS CloudWatch

  • AWS DataSync

• Experience developing and maintaining ETL/ELT or data integration pipelines.

• Understanding of data warehousing concepts and database design.

• Strong troubleshooting and problem-solving skills.

• Good understanding of cloud security, access management, and data protection practices.

• Ability to work independently while collaborating effectively with cross-functional teams.

Preferred Qualifications

• Experience with AWS-based data architecture and cloud data platforms.

• Experience with data quality, validation, and monitoring practices.

• Familiarity with CI/CD, Git, and infrastructure-as-code tools.

• Experience optimizing AWS data workloads for performance and cost.

• AWS certifications related to Data Engineering, Cloud, or Solutions Architecture are a plus.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.

• Develop and optimize SQL queries for data transformation, analysis, and reporting.

• Build and maintain data processing solutions using Python.

• Manage and organize data stored in Amazon S3.

• Develop and maintain data warehouse solutions using Amazon Redshift.

• Configure and manage AWS IAM roles, users, and policies following security best practices.

• Develop and maintain data integration and ETL workflows using AWS Glue.

• Monitor data pipelines, applications, and AWS resources using Amazon CloudWatch.

• Implement and manage data transfer and synchronization processes using AWS DataSync.

• Troubleshoot data pipeline failures, performance issues, and data quality problems.

• Work with software engineers, analysts, and other stakeholders to understand data requirements and deliver reliable data solutions.

• Document data pipelines, processes, configurations, and technical procedures.

• Follow best practices for data security, access control, reliability, and scalability.