Mid-Level Data Engineer (On-site)

About the Role

We are seeking a Mid-Level Data Engineer to join our team in Pasay, National Capital Region (NCR). This on-site position offers an opportunity to design, build, and maintain data pipelines on Google Cloud Platform. You will play a crucial role in transforming and analyzing data to support our business objectives. If you have a strong background in SQL, Python, and data engineering, we encourage you to apply.

Responsibilities

• Design, build, and maintain ETL/ELT data pipelines on Google Cloud Platform.
• Write efficient, production-grade SQL for data transformation and analysis.
• Develop and maintain Python-based data processing scripts.
• Build and manage workflow orchestration using Apache Airflow.
• Support and maintain data models and dashboards in Looker.
• Implement data quality checks and monitoring for pipelines.
• Collaborate with analysts and stakeholders to understand data needs.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
• At least 2 years of hands-on experience in data engineering or a similar role.
• Strong SQL and Python skills.
• Hands-on experience with cloud platforms, preferably Google Cloud Platform.
• Experience with workflow orchestration tools, ideally Apache Airflow.

Benefits

We offer a competitive salary and a supportive work environment. Enjoy work-life balance with weekends off and opportunities for professional growth. Our benefits include health maintenance organization (HMO) coverage and flexible working arrangements. Join us to advance your career in data engineering while contributing to impactful projects.

For more information on our company culture and other roles, visit our careers page or check our salary insights.

• Bachelor's degree in a relevant field.
• 2+ years of data engineering experience.
• Proficient in SQL and Python.
• Experience with Google Cloud Platform.
• Familiarity with Apache Airflow.

• Design and maintain ETL/ELT pipelines.
• Write production-grade SQL for data analysis.
• Develop Python scripts for data processing.
• Manage workflows using Apache Airflow.
• Support data models in Looker.
• Implement data quality checks.