Data Engineer (Hybrid)
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Summary
Data Engineer building and maintaining ETL/ELT pipelines and data infrastructure for reliable enterprise data delivery, monitoring pipeline performance and data quality SLAs, and applying CI/CD, version control, and data modeling best practices. Stack centers on SQL, Python, cloud data platforms (AWS/GCP/Azure), and orchestrators like Airflow or Dagster. Hybrid role in Mandaluyong City.
Data Engineer
- Role Summary: Responsible for constructing and maintaining robust ETL/ELT pipelines and data infrastructure to ensure reliable enterprise data delivery.
- Key Responsibilities:
- Build, optimize, and maintain automated data pipelines using orchestration tools.
- Monitor pipeline performance, uptime, and data quality SLAs.
- Apply engineering best practices including CI/CD, version control, and data modeling.
- Qualifications:
- 2–3 years of experience in data engineering or analytics engineering.
- Strong proficiency in SQL and Python.
- Experience with cloud data platforms (AWS, GCP, or Azure) and orchestration tools (Airflow, Dagster, etc.).
- Location & Setup: Hybrid – Mandaluyong City