Data Engineer [Snowflake, BigQuery, GCP]

NCS Philippines; Taguig; Hybrid; PHP 900,000 - 1,300,000; Full time

Job summary

NCS Philippines is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and data assets in a cloud-first environment. You will transform raw data into actionable insights and support analytics, reporting, and automation initiatives.

You will collaborate with cross-functional teams to gather requirements, implement data governance, and deliver reliable data products that drive business decisions in a dynamic setting.

Qualifications

• Experience with designing and building data pipelines.
• Knowledge of data modeling and ETL processes.
• Familiarity with cloud data platforms.

Responsibilities

• Design, build, and maintain scalable, secure data pipelines and storage systems with data quality checks.
• Implement data governance to ensure integrity and accessibility.
• Develop data models and databases and communicate architecture effectively.
• Create and maintain scripts to automate data processing and pipelines.
• Develop data visualization and reporting to enable insights for stakeholders.
• Collaborate with cross-functional teams to gather data requirements and deliver ad hoc reports.

Skills

Snowflake

BigQuery

GCP

Job description

MAIN REQUIREMENTS:

• Snowflake
• BigQuery
• GCP

GENERAL RESPONSIBILITIES:

The Data Engineer will be responsible for designing, building, and maintaining robust data infrastructure and pipelines that support current and future business needs. This includes transforming raw data into actionable insights through scalable and secure pipelines, managing data assets effectively, and enabling seamless access to data for analytical and operational processes. The Data Engineer will collaborate with cross-functional teams to address data requirements, optimize workflows, and deliver impactful solutions through automation, visualization, and reporting.

DUTIES AND RESPONSIBILITIES:

• Design, build, and maintain scalable, secure data pipelines and storage systems; ensure data quality through ETL processes and regular checks.
• Implement policies and practices to control, optimize, and secure data assets, ensuring data integrity and accessibility.
• Develop and maintain data models, structures, and databases to meet business needs; communicate data architecture effectively.
• Develop, test, and maintain scripts and programs to automate data processing and pipelines, adhering to industry standards.
• Create and operationalize data visualization solutions to simplify complex data for stakeholders and decision-making.
• Work with cross-functional teams to gather data requirements, optimize existing processes, and deliver ad hoc reports and insights