Senior Data Engineer [Remote / US]
Summary
Designs, builds, and maintains scalable cloud data platforms on GCP — building ETL/ELT pipelines into BigQuery, transformation workflows with dbt, orchestration in Airflow, and Looker dashboards to power analytics, BI, and operational reporting. Remote from the Philippines on a night-shift schedule.
Remote | Philippines | Night Shift
About the role
We are looking for a highly skilled Data Engineer to design, build, and maintain scalable data platforms that support analytics, business intelligence, and operational reporting. In this role, you will be responsible for developing robust data pipelines, optimizing cloud-based data infrastructure, and ensuring high-quality, reliable datasets that drive critical business decisions.
You will work closely with software engineers, analytics teams, architects, and business stakeholders to build and maintain a modern data ecosystem utilizing Google Cloud Platform (GCP) technologies including BigQuery, AlloyDB, Airflow, dbt, and Looker.
Key responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines from multiple data sources into BigQuery
Build and optimize data integrations that support operational and analytical workloads
Implement data transformation workflows using dbt to create clean, reliable, and analytics-ready datasets
Develop and maintain data orchestration workflows using Airflow
Ensure data platforms are scalable, secure, performant, and cost-efficient
Design and maintain logical and physical data models to support reporting and analytics requirements
Create reusable data marts and aggregate datasets for business intelligence and reporting
Develop and support Looker models, dashboards, and self-service analytics capabilities
Establish data validation, monitoring, and quality assurance processes
Monitor pipeline performance, data freshness, and system reliability
About you
4+ years of experience in Data Engineering or a related field
Strong SQL expertise, including performance optimization and complex query development
Hands-on experience with BigQuery and large-scale cloud data platforms
Experience with AlloyDB, PostgreSQL, or similar relational databases
Advanced Python skills for data processing, automation, and pipeline development
Experience building ETL/ELT pipelines using dbt and Airflow
Strong understanding of data modeling principles and best practices
Experience with Looker or equivalent BI tools
Strong understanding of data quality, governance, and monitoring frameworks
Experience using Git and CI/CD workflows