Data Engineer
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Summary
On-site Data Engineer in Mandaluyong City to build, deploy, and maintain data pipelines and infrastructure supporting data-driven products, monitoring reliability and data quality alongside data scientists and cross-functional teams. Core stack: Python, SQL, ETL/ELT, cloud platforms (AWS preferred), and orchestration tools like Airflow or Dagster.
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.