Data Engineer

Pay&Go (BTI Payments Phils, Inc.); Makati; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

Pay&Go (BTI Payments Phils, Inc.) is seeking a Data Engineer to build and strengthen our data infrastructure supporting analytics, reporting, and digital financial services in Metro Manila. You’ll apply core data-engineering fundamentals and learn new technologies in a hands-on environment.

You’ll build and maintain ETL/ELT pipelines, optimize SQL queries, support data warehousing and modeling, and collaborate with cross-functional teams to deliver reliable data solutions for reporting and

Qualifications

• At least 3 years of relevant Data Engineering experience.
• Strong SQL skills with query optimization and relational databases.
• Practical experience building and maintaining ETL/ELT pipelines.
• Working knowledge of Python for data processing and automation.
• Good understanding of data warehousing, data modeling, and data quality.
• Experience troubleshooting data-pipeline failures and reconciling data discrepancies.
• Familiarity with Git or other version-control tools.
• Good communication and documentation skills for technical and business stakeholders.

Responsibilities

• Build, maintain, and optimize ETL/ELT data pipelines
• Work with relational databases and develop efficient SQL queries
• Support data warehousing, data modeling, and data-quality initiatives
• Investigate pipeline failures, reconcile data discrepancies, and perform root‑cause analysis
• Use Python for data processing and automation
• Help ensure data accuracy, reliability, and availability for reporting and analytics
• Maintain clear technical documentation and support data lineage and metadata requirements
• Collaborate with technical teams and business stakeholders in delivering reliable data solutions
• Work within version‑control and development practices for data solutions

Skills

SQL

ETL/ELT pipelines

Python

Git

Communication

Tools

Azure Data Factory

PySpark

Apache Spark

Kafka

Job description

We’re looking for aData Engineerwith strong core data-engineering fundamentals to help us build and strengthen the data infrastructure supporting our analytics, reporting, and digital financial services.

You don’t need to come in knowing every platform or technology in our environment. What matters most is a solid foundation in data engineering, hands‑on problem-solving skills, and the ability to learn and work with new technologies.

What You’ll Do

• Build, maintain, and optimize ETL/ELT data pipelines
• Work with relational databases and develop efficient SQL queries
• Support data warehousing, data modeling, and data‑quality initiatives
• Investigate pipeline failures, reconcile data discrepancies, and perform root‑cause analysis
• Use Python for data processing and automation
• Help ensure data accuracy, reliability, and availability for reporting and analytics
• Maintain clear technical documentation and support data lineage and metadata requirements
• Collaborate with technical teams and business stakeholders in delivering reliable data solutions
• Work within version‑control and development practices for data solutions

What We’re Looking For

• At least3 years of relevant experience in Data Engineering, database development, or a similar role
• StrongSQL skills, including query optimization and relational databases
• Practical experience building and maintainingETL/ELT pipelines
• Working knowledge ofPython for data processing and automation
• Good understanding of data warehousing, data modeling, and data‑quality principles
• Experience troubleshooting data-pipeline failures and reconciling data discrepancies
• Familiarity withGit or other version‑control tools
• Good communication and documentation skills, with the ability to work with both technical and business stakeholders

An Advantage, But Not Required

• Microsoft Fabric, Azure Data Factory, or similar cloud data platforms
• PySpark, Apache Spark, or distributed data processing
• Kafka, event streaming, or near‑real‑time data pipelines
• Lakehouse architecture
• CI/CD and DevOps practices for data pipelines
• Data governance, lineage, metadata management, and access controls
• Banking, payments, fintech, or other financial services experience

Don’t tick every box?

If you have strong Data Engineering fundamentals and the ability to learn new technologies, we still encourage you to apply. Platform‑specific tools in our environment can be learned on the job.