Data Engineer

White Cloak Technologies, Inc.; Philippines; On-site; PHP 600,000 - 1,000,000; Full time

Job summary

White Cloak Technologies, Inc. is seeking a Data Engineer in the Philippines to help build scalable data solutions. You will design ETL/ELT pipelines with Databricks and AWS, transforming raw data into business-ready datasets and supporting reporting needs.

You will collaborate with business and IT teams to ensure data quality, automate workflows, and optimize data warehouses and lakes for performance and reliability. Strong SQL and Python skills are essential.

Qualifications

• 3+ years of data engineering, ETL development, or related role.
• Hands-on Databricks experience for building or maintaining pipelines.
• Experience with AWS services for storage, processing, or integration.
• Strong SQL skills including optimization and transforms.
• Proficiency in Python for data engineering and automation.
• Experience building ETL/ELT pipelines from multiple sources.
• Familiarity with APIs, data modeling, and data quality best practices.
• Experience with GitHub or other version control tools.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks and AWS.
• Build and optimize data workflows that ingest, transform, and load data from various internal and external sources.
• Integrate data from databases, APIs, cloud storage, and third-party applications.
• Develop and optimize SQL queries and Python scripts for efficient data processing.
• Maintain and improve data warehouses and data lake environments to ensure performance, reliability, and scalability.
• Monitor data quality, troubleshoot pipeline issues, and implement validation processes.
• Collaborate with business stakeholders and IT teams to understand reporting and analytics requirements.
• Support Power BI reporting by preparing clean and well-structured datasets.
• Document data pipelines, workflows, and technical processes.
• Participate in testing and production deployment to ensure stable and reliable data solutions.

Skills

Databricks

SQL

Python

ETL pipelines

Data modeling

Data quality

GitHub

Tools

Databricks

AWS

Job description

We are looking for a Data Engineer to join and support the development and optimization of scalable data solutions. This role is ideal for someone with hands‑on experience building data pipelines using Databricks and AWS, and who enjoys transforming raw data into reliable, business‑ready datasets.

You will collaborate with business and technical teams to integrate data from multiple sources, automate workflows, and ensure high-quality data is available for reporting and analytics.

Responsibilities:

• Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks and AWS.

• Build and optimize data workflows that ingest, transform, and load data from various internal and external sources.

• Integrate data from databases, APIs, cloud storage, and third‑party applications.

• Develop and optimize SQL queries and Python scripts for efficient data processing.

• Maintain and improve data warehouses and data lake environments to ensure performance, reliability, and scalability.

• Monitor data quality, troubleshoot pipeline issues, and implement validation processes.

• Collaborate with business stakeholders and IT teams to understand reporting and analytics requirements.

• Support Power BI reporting by preparing clean and well‑structured datasets.

• Document data pipelines, workflows, and technical processes.

• Participate in testing and production deployment to ensure stable and reliable data solutions.

Qualifications:

• At least 3 years of experience in Data Engineering, ETL Development, or a related role.

• Hands‑on experience using Databricks for developing or maintaining data pipelines.

• Experience working with AWS services for data storage, processing, or integration.

• Strong SQL skills, including query optimization and data transformation.

• Proficiency in Python for data engineering and automation.

• Experience building ETL/ELT pipelines and integrating multiple data sources.

• Familiarity with APIs, data modeling, and data quality best practices.

• Experience with GitHub or other version control tools.