Data Engineer (Hybrid)
Summary
Designs, builds, and maintains scalable ETL/ELT pipelines and data warehouse/lakehouse infrastructure supporting analytics, regulatory reporting, and digital financial services. Core stack: Microsoft Fabric, MS SQL Server/T-SQL, Python/PySpark, Kafka streaming, and dimensional data modeling.
About the Company:
BTI Payments Philippines, Inc., is an independent diversified payments technology provider. We are accredited by the Bangko Sentral ng Pilipinas (BSP) as Operator for Payment System, and BancNet as Independent ATM deployer.
To date, we own and manage over 4,000 Pay & Go kiosks and 39 Cash Connect ATM machines nationwide.
We are a wholly owned subsidiary of Banktech – a leader in ATM and payment technology in Australia for 25 years, bringing decades expertise and experience into transactions processing and payment device management, across Australia and Asia.
About the Role:
We are looking for a highly skilled Data Engineer with experience in banking or fintech environments to design, build, and maintain scalable data infrastructure that supports enterprise analytics, regulatory reporting, and digital financial services.
The role will focus on data architecture, data modeling, and integration development, including pipelines that integrate data from multiple sources and optimize data warehouse and lakehouse platforms. The goal is to deliver secure, high-quality, and reliable data outputs for dashboards, reports, regulatory submissions, and decision-making.
The ideal candidate has strong experience with Data Fabric frameworks, Microsoft Fabric or cloud-based data platforms, SQL-based data warehousing, Python/PySpark scripting, streaming technologies, and dimensional and relational data modeling, with a solid understanding of financial data structures, data governance, compliance, and regulatory requirements.
Key Responsibilities:
Collaborate with business stakeholders, data analysts, and reporting teams to translate business and regulatory requirements into scalable data models, pipelines, and trusted datasets.
Design and build scalable frameworks for data ingestion, transformation, orchestration, and data modeling to support high-volume transactional, operational, and financial analytics workloads.
Develop and maintain ETL/ELT pipelines supporting batch, near-real-time, and streaming integration into the enterprise data platform.
Perform data investigation, root-cause analysis, and performance optimization for ETL/ELT pipelines, reports, and downstream data products.
Implement data quality validation, monitoring, reconciliation, and auditing mechanisms to maintain warehouse reliability, completeness, and performance.
Maintain clear documentation for data lineage, metadata, data architecture, pipeline logic, and operational support procedures.
Partner with Project Managers, Business Analysts, QA Engineers, Operations Support, and third‑party partners to deliver reliable, production‑ready data solutions.
Support DevOps practices for data pipelines, including version control, CI/CD, deployment coordination, monitoring, and incident resolution.
Participate in Agile delivery activities, including sprint planning, stand‑ups, reviews, and retrospectives.
Qualifications:
Education: Graduate of BS Computer Science, BS Information Technology, BS Information Systems, and other IT related courses.
Experience: At least 5 years of experience in data warehousing, data integration, ETL/ELT development, or enterprise data platform solutions.
Skills:
Strong experience with Data Fabric architecture or data integration frameworks particular on Microsoft Fabric or comparable cloud‑based data platforms
Proficient in MS SQL Server and T‑SQL/SQL scripting; experience with Python, PySpark, Apache Spark, Kafka or streaming technologies, and Parquet file formats.
Experience designing and maintaining enterprise data warehouse, lakehouse, and data mart solutions, including Data Lake, OneLake, Lakehouse, Data Warehouse, and Data Marts.
Strong understanding of dimensional and relational data modeling, data lineage, metadata management, and data governance practices.
Working knowledge of DevOps practices for data pipelines, including GitHub or equivalent version control, CI/CD, release management, and deployment controls.
Preferred: Experience with financial services, regulatory reporting, audit controls, data privacy, access controls, and compliance-driven data environments.
Why Join Us?
Be part of a growing data‑driven organization
Collaborative and fast‑paced team culture
Benefits and Perks
Generous Leave Credits
Allowances
Hybrid Set-up
HMO Day 1