Senior Data Engineer - Cloud Data Platform & AI Pipelines

PCS Wireless, LLC.

Makati

Hybrid

PHP 1,200,000 - 2,200,000

Full time

14 days+

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Job summary

PCS Wireless, LLC. seeks a Senior Data Engineer to own and advance our data platform, pipelines, and data models across inventory, purchasing, and sales. You will work with ERP systems like NetSuite, strengthen our data warehouse, and guide cloud data strategy while mentoring junior engineers.

You will build robust ETL/ELT processes, optimize SQL Server storage, and ensure reliable reporting with Power BI. Hybrid role based in Makati, Philippines, with 3 days in-office and US Eastern working

Qualifications

Bachelor's degree in computer science, math, software engineering, or a related field.
5+ years of data engineering experience building and owning production data pipelines.
4+ years writing production T-SQL — stored procedures, performance tuning, and legacy code understanding.
2+ years PySpark and Delta Lake experience.
Experience against ERP sources (NetSuite, SAP, Oracle EBS, or Dynamics).
Experience with on-premises to cloud data migrations and data validation.
Strong data reconciliation skills and ability to explain issues to finance stakeholders.
Nice-to-have: Microsoft Fabric, Databricks, Azure Synapse, Snowflake; Power BI and DAX; Azure fundamentals; Claude Code usage; AI-driven workflows; MCP servers.
Retail/distribution/manufacturing background preferred with inventory, POs, and COGS understanding.
Ownership mindset, adaptability, knowledge sharing, and collaboration.

Responsibilities

Build and optimize data pipelines from ERP and sources into the data warehouse.
Develop ETL/ELT processes using T-SQL, Spark, and PySpark.
Maintain and refactor SQL Server warehouse logic as architecture evolves.
Design data models for inventory, purchasing, sales, and device lifecycle.
Create data quality controls and reconciliation checks between source and target.
Support Power BI semantic models, measures, and refresh reliability.
Troubleshoot end-to-end from source to dashboard and resolve root causes.
Contribute to cloud data platform strategy (Fabric, Databricks, Synapse).
Plan data migration and modernization efforts with validation and parity testing.
Define data schemas and guardrails for responsible AI and data access.
Mentor junior engineers and document architecture and processes.