Data Engineer

Our Clients; Mandaluyong; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

Our Clients is seeking a Data Engineer to build, maintain, and optimize data pipelines and infrastructure that power data-driven products and initiatives.

You will collaborate with data scientists, engineers, and cross-functional teams to ensure data is accurate, accessible, and reliable for analysis and product development.

Qualifications

• 2–3 years of relevant data engineering or related experience.
• Proficiency in Python and SQL.
• Experience with cloud data platforms and ETL pipelines.

Responsibilities

• Develop, deploy, and maintain data pipelines that support business use cases and product features.
• Monitor pipeline performance and reliability, troubleshoot data quality issues, and help resolve operational incidents.
• Support data requests and pipeline incidents within agreed timelines and service-level expectations.
• Implement data validation, testing, and monitoring practices to maintain data accuracy and reliability.
• Maintain clear technical documentation and follow established development and deployment procedures.
• Apply data engineering best practices, including version control, CI/CD, data governance, and observability.
• Collaborate with senior engineers and cross-functional stakeholders on data initiatives and continuous improvement.
• Identify opportunities to enhance pipeline performance, reliability, and usability.

Skills

Python

SQL

Data pipelines

Education

Bachelor's degree in Computer Science, IT, Engineering, Mathematics, or related field

Tools

AWS

GCP

Azure

Apache Airflow

Dagster

Job description

We're looking for a motivated Data Engineer to help build, maintain, and improve data pipelines and infrastructure that support data-driven products and business initiatives.

In this role, you'll work alongside experienced data engineers, data scientists, and cross-functional teams to ensure data is accurate, accessible, reliable, and ready for use.

Key Responsibilities

• Develop, deploy, and maintain data pipelines that support business use cases and product features.
• Monitor pipeline performance and reliability, troubleshoot data quality issues, and help resolve operational incidents.
• Support data requests and pipeline incidents within agreed timelines and service-level expectations.
• Implement data validation, testing, and monitoring practices to maintain data accuracy and reliability.
• Maintain clear technical documentation and follow established development and deployment procedures.
• Apply data engineering best practices, including version control, CI/CD, data governance, and observability.
• Collaborate with senior engineers and cross-functional stakeholders on data initiatives and continuous improvement.
• Identify opportunities to enhance pipeline performance, reliability, and usability.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related field, or equivalent practical experience.
• 2–3 years of relevant experience in Data Engineering, Analytics Engineering, Software Engineering, or a related technical role.
• Proficiency in Python, including scripting and basic data processing.
• Solid SQL skills, including querying, filtering, aggregations, and joins.
• Experience with relational databases, data warehousing, and ETL/ELT pipelines.
• Hands-on experience with at least one cloud platform: AWS (preferred), GCP, or Azure.
• Experience with a data orchestration tool such as Apache Airflow, Dagster, or an equivalent platform.
• Ability to write maintainable code, document technical processes, and collaborate effectively with a team.
• Willingness to learn new technologies and continuously improve engineering practices.