Data Modeler / Data Engineer

SYSGEN RPO; Philippines; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

SYSGEN RPO is seeking a data engineer to architect and build end-to-end data pipelines across diverse source systems. You will land and stage raw data in modern cloud platforms, orchestrate workloads, and refine the SQL layer for reporting and performance.

The role requires hands-on experience with cloud platforms (Fabric, Databricks, Snowflake), REST API integration, and strong data-validation discipline to ensure accuracy before reporting.

Qualifications

• Expert SQL with complex queries and tuning.
• Hands-on with modern cloud data platforms (lakehouse/warehouse).
• API integration experience with REST, OAuth, pagination.
• Proven data-validation discipline.

Responsibilities

• Architect and build end-to-end data pipelines across companies with assorted source systems.
• Land and stage raw source data in modern cloud data platforms with orchestration, scheduling, monitoring, and failure recovery.
• Build and tune the SQL layer: load orchestration, reporting views, incremental vs. full-refresh strategies, performance optimization.
• Develop semantic models and measures for BI consumption; manage deployments, refresh schedules, and access security.
• Integrate financial data from accounting systems and reporting packages; reconcile operational data against finance-reported actuals.
• Build validation and data-quality frameworks: automated tie-outs against source-system reports, pipeline health monitoring, and exception reporting that routes fixes back to operating teams.

Skills

SQL

Dimensional modeling

Cloud data platform

REST API integration

Python scripting

Data validation

Tools

Microsoft Fabric

Databricks

Snowflake

Job description

• Architect and build end-to-end data pipelines across companies with assorted source systems: REST API extractions, scheduled and incremental loads, database replication feeds, and flat-file/ERP ingestion
• Land and stage raw source data in modern cloud data platforms (lakehouse/warehouse architectures), with orchestration, scheduling, monitoring, and failure recovery
• Build and tune the SQL layer: load orchestration, reporting views, incremental vs. full-refresh strategies, performance optimization
• Develop semantic models and measures for BI consumption; manage deployments, refresh schedules, and access security
• Integrate financial data from accounting systems and reporting packages; reconcile operational data against finance-reported actuals
• Build validation and data-quality frameworks: automated tie-outs against source-system reports, pipeline health monitoring, and exception reporting that routes fixes back to operating teams

Skills and Experience:

• Expert SQL (complex queries, tuning, stored procedures) and strong dimensional-modeling fundamentals
• Hands-on experience with a modern cloud data platform (e.g., Microsoft Fabric, Databricks, Snowflake) - lakehouse/warehouse patterns, pipelines, notebooks
• API integration: REST extraction, auth flows (OAuth, service principals), pagination and rate-limit handling; scripting in Python
• Proven data-validation discipline - numbers tie to source before anyone has to ask