Data Engineer( up to 200K php)

Keyrus; Metro Manila; On-site; PHP 700,000 - 900,000; Full time

Job summary

Keyrus in the Philippines is seeking a Data Engineer for their Enterprise Data Platform. The successful candidate will work closely with architects and analysts to implement data pipelines aligned with business requirements.

This role involves developing reusable ETL pipelines and optimizing data transformation logic. Ideal candidates should have hands-on experience with Airflow and dbt Core and a solid understanding of data quality processes.

Qualifications

• Hands-on experience in data engineering, ETL development, and data lakehouse implementation.
• Experience with Airflow for orchestration.
• Experience with dbt Core for transformation development, testing, and documentation.

Responsibilities

• Develop reusable ETL pipelines using Airflow and dbt Core.
• Implement Bronze → Silver → Gold data transformation flows based on signed-off designs.
• Optimize transformation logic and data models for query efficiency.

Skills

Data engineering

ETL development

Airflow

dbt Core

GitLab

Job description

Job Description: Data Engineer – Enterprise Data Platform

Role Summary: The Data Engineer will work closely with data architects, business analysts, governance teams, platform teams, and project stakeholders to implement data pipelines and data models aligned with signed‑off BRD, FRS, and Low‑Level Design documents.

Key Responsibilities

• Develop reusable ETL pipelines using Airflow and dbt Core.
• Build SQL‑based transformation models using dbt-spark or an agreed adapter.
• Implement Bronze → Silver → Gold data transformation flows based on signed‑off designs.
• Develop data cleansing, standardization, aggregation, matching, and enrichment logic for platform and business use cases.
• Support ETL exception handling, retry logic, audit logging, and operational monitoring.
• Implement logical and physical data models across Bronze, Silver, and Gold layers.
• Optimize transformation logic and data models for query efficiency, scalability, and maintainability.
• Implement embedded data quality checks in ingestion and ETL processes.
• Support integration of data quality outputs, metadata, and lineage artifacts with Alation.
• Generate dbt artifacts and metadata needed for cataloging and lineage visibility.
• Ensure data engineering outputs are traceable, governed, and aligned with access and classification requirements.

CI/CD and Deployment

• Use GitLab for version control, code review, and CI/CD pipeline execution.
• Support deployment of Airflow DAGs, dbt models, scripts, and configuration across Development, UAT, and Production environments.
• Maintain deployment scripts, technical documentation, and runbooks.

Required Skills and Experience

• Hands‑on experience in data engineering, ETL development, and data lakehouse implementation.
• Experience with Airflow for orchestration.
• Experience with dbt Core for transformation development, testing, and documentation.
• Experience using GitLab or equivalent version control and CI/CD tool.
• Understanding of data quality checks, audit logging, lineage, and catalog integration.