Data Engineer: Build Scalable Data Pipelines & Insights

OmniQuest, Inc.; Mandaluyong; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

OmniQuest, Inc. is seeking a Data Engineer to help build a scalable data ecosystem, delivering accurate, timely, and well-structured data to enable data asset enrichment across the enterprise.

You will work with data scientists, engineers, and product teams to implement reliable data pipelines and supporting infrastructure. The role emphasizes collaboration, documentation, governance, and observability, with opportunities to improve CI/CD, data quality, and tooling with Airflow/Dagster, Docker,

Qualifications

• Bachelor’s degree or equivalent practical experience in a technical field.
• 2–3 years in data engineering, analytics engineering, or related role.
• Strong Python and SQL skills with experience in data warehousing and ETL/ELT pipelines.
• Experience with at least one cloud platform (AWS, GCP, Azure).
• Experience with data orchestration tools (Dagster, Airflow).
• Ability to write maintainable code and documentation, and willingness to learn new tools.

Responsibilities

• Develop and deploy data pipelines for priority use cases and features.
• Monitor uptime and address data quality issues as per SLAs.
• Respond to data requests and incidents within defined deadlines.
• Ensure reliable pipeline execution through tested CI/CD and governance practices.
• Maintain technical documentation and basic test coverage for pipelines.
• Collaborate on cross-functional projects and knowledge sharing.

Skills

Python scripting

SQL querying

Data pipeline concepts

Documentation

Education

Bachelor’s degree in Computer Science, Information Technology, Engineering, Mathematics, or related field

Tools

Dagster

Airflow

Git

Docker

Terraform

Alembic

dbt

Job description

OmniQuest, Inc. is seeking a Data Engineer to help build a scalable data ecosystem, delivering accurate, timely, and well-structured data to enable data asset enrichment across the enterprise.

You will work with data scientists, engineers, and product teams to implement reliable data pipelines and supporting infrastructure. The role emphasizes collaboration, documentation, governance, and observability, with opportunities to improve CI/CD, data quality, and tooling with Airflow/Dagster, Docker,