Data Engineer

The Data Engineer plays a critical role in designing, developing, and maintaining data infrastructure to collect, integrate, and prepare data from multiple sources—such as CRM, sales systems, websites, LINE OA, social media, and advertising platforms.

The role ensures that data is accurate, accessible, and standardized across the organization, enabling effective analysis, dashboard development, and data-driven decision-making for Marketing, Sales, and executive teams.

The ultimate goal is to build an end-to-end data connection across the customer journey: Marketing → Lead → Sales → Revenue.

Key Responsibilities

• Design, develop, and maintain data pipelines to collect, integrate, and process data from multiple sources.
• Develop and maintain ETL/ELT processes to ensure data is accurate, timely, and ready for analysis.
• Integrate data from CRM, sales systems, call centers, websites, LINE OA, social media, and advertising platforms through databases and APIs.
• Design and develop data warehouses, data lakes, and data models tailored to each department’s business needs.
• Monitor and improve data quality, including accuracy, completeness, duplication, and consistency across systems.
• Ensure data security, data governance, and appropriate access-control policies.
• Create and maintain documentation for data architecture, data flows, and data-management processes.
• Support analysis of marketing campaign performance, conversion funnels, leads, and sales performance.
• Collaborate with Data Analysts, Marketing, Sales, CRM, and IT teams to prepare data for dashboards, reports, and business analytics.
• Support end-to-end customer journey data integration: Marketing → Lead → Sales → Revenue.
• Monitor, troubleshoot, and resolve issues related to data pipelines, databases, and data infrastructure.
• Perform other duties as assigned.

Qualifications

• Bachelor’s degree or higher in Computer Science, Computer Engineering, Information Technology, Data Science, or a related field.
• At least 1-2 years of experience in Data Engineering, Data Management, or Data Infrastructure.
• Strong proficiency in SQL, database management, and data modeling.
• Proficiency in Python programming.
• Hands-on experience with ETL/ELT processes, data pipelines, and API integration.
• Knowledge of data warehouses, data lakes, and cloud platforms.
• Experience with marketing data, CRM, websites, social media, or advertising platforms will be considered an advantage.
• Strong communication, coordination, problem-solving, and analytical skills.
• Ability to work effectively under pressure and manage time efficiently.

Hard Skills

• SQL and database management
• Python programming
• ETL/ELT processes and data pipeline development
• API integration and data modeling
• Data warehouse and data lake concepts
• Cloud platforms, such as GCP, AWS, or Azure
• Experience with tools such as BigQuery, Airflow, dbt, Snowflake, or Databricks is an advantage

Soft Skills

• Strong communication and coordination skills
• Ability to collaborate effectively with both technical and business teams
• Analytical thinking and problem-solving skills
• Strong attention to detail in data management
• Accountability and systematic work-management skills