Data Engineer
Summary
Builds and maintains scalable data pipelines and ETL processes in AWS using Python and SQL to ensure reliable analytics and data availability.
Job Description:
- Design, build, and maintain scalable data pipelines and ETL processes to support analytics and business operations.
- Develop data processing scripts and automation using Python to ingest, transform, and validate datasets.
- Design and optimize SQL queries, schemas, and data models for performance and reliability.
- Deploy and manage data workloads in AWS environments ensuring security, monitoring, and scalability.
- Collaborate with analysts, developers, and business teams to ensure data accuracy, availability, and governance compliance
Qualifications:
- Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or any related course.
- 3–5 years of experience in data engineering, data pipeline development, or backend data processing.
- Strong proficiency in Python for data processing and automation.
- Advanced knowledge of SQL, data modeling, and relational database optimization.
- Hands-on experience with AWS data services (e.g., S3, RDS, Glue, Lambda, or similar).
- Experience building ETL pipelines and handling structured and semi-structured data.
- Familiar with version control, CI/CD workflows, and Agile methodologies.
- Strong analytical mindset with good documentation and communication skills.
- Can work fully onsite at Ortigas