Data Engineer (DBT / Hybrid 2x a week onsite)

Are you a Data Engineer with strong DBT experience looking to work on large-scale, high-impact data platforms?

We are looking for a modern data engineer who operates in a cloud-native, data-as-code environment built on AWS, with a focus on scalable and real-time data processing.

The ideal candidate has hands-on experience with DBT for transformations, Apache Airflow for orchestration, and Python for building production-grade data pipelines. Experience with modern streaming technologies such as Kafka, Spark, or Flink is a strong advantage.

This role suits engineers who think like software developers—comfortable with version control, CI/CD, testing, and distributed systems—rather than traditional ETL or legacy data warehouse practitioners.

Work Setup

• Hybrid: 2x onsite per week
• Office Location: Mandaluyong (Rockwell Business Center, Sheridan)
• Schedule: Monday to Friday, 10:00 AM to 7:00 PM

What You’ll Do

• Design, build, and maintain scalable data pipelines integrating internal and external data sources
• Develop batch and real-time data processing workflows
• Build, optimize, and maintain DBT models, tests, macros, and documentation
• Develop data integrations with CRM, marketing, and financial platforms
• Ensure data quality, reliability, and observability through validation and monitoring frameworks
• Build data APIs and services for internal and external consumption
• Troubleshoot and resolve production issues
• Work closely with Product, BI, Engineering, and Infrastructure teams
• Participate in code reviews and Agile ceremonies

Must-Have Qualifications

• Strong hands-on experience with DBT (models, tests, macros, documentation) (Main Qualification)
• Proven experience building and maintaining data pipelines using DBT and Apache Airflow
• Experience with streaming/real-time technologies such as Kafka, Spark, or Flink
• Strong programming skills in Python and/or Java
• Advanced SQL skills and database experience (MySQL, PostgreSQL, MongoDB, Elasticsearch)
• Experience working with AWS cloud services
• Strong understanding of modern data architectures (Data Lakes / Lakehouse)
• Experience building APIs / REST services
• Strong data modelling and data quality practices
• Excellent communication and collaboration skills

Nice to Have

• Exposure to AI-assisted development tools (Cursor, Claude)
• Experience with marketing data (campaigns, rewards, segmentation)
• Work experience under gaming or gambling industry