Senior Data Engineer - Philippines (Hybrid)

About the Role:

As a Senior Data Engineer, you will own and advance our data and analytics platform — the pipelines, warehouse, and data models that carry inventory, purchasing, sales, and device data across the business. You will work directly with our ERP and source systems, strengthen and modernize our existing data warehouse, and ensure the numbers our teams rely on are accurate and trusted. As our platform evolves, you will help evaluate and shape our cloud data strategy and lead modernization initiatives as they are defined.

What you will do:

• Build, own, and optimize data pipelines from our ERP (NetSuite) and other source systems into our data warehouse.
• Develop and maintain robust ETL/ELT processes using T-SQL and modern data engineering tooling, including Spark and PySpark where applicable.
• Maintain, tune, and improve existing SQL Server stored procedures and warehouse logic, and refactor them as our architecture evolves.
• Design and maintain data models covering inventory, purchasing, sales, and device lifecycle at transaction and serial-number grain.
• Build reconciliation and data-quality controls that detect discrepancies between source and target before a business user finds them in a report.
• Support the reporting layer — Power BI semantic models, measures, and refresh reliability — and the analysts who depend on it.
• Troubleshoot end to end, from the source system through the pipeline and warehouse to the number on the dashboard, and resolve the root cause.
• Contribute to the evaluation and design of our future cloud data platform, including modern lakehouse architectures such as Microsoft Fabric, Databricks, or Azure Synapse.
• Help plan and execute data migration and modernization initiatives as they are approved, including cutover planning, parity testing, and validation.
• Define data schemas and structures to support efficient data management and reporting.
• Identify, communicate, and mitigate the assumptions, issues, and risks that occur throughout the project lifecycle.
• Implement best practices for data engineering, including coding standards and testing, while developing and maintaining documentation for data architecture, processes, and tools.
• Continuously evaluate new technologies and tools that could improve the reliability, performance, and cost of our data platform.
• Use AI tools such as Claude and Claude Code day to day to speed up SQL and PySpark development, code review, documentation, and troubleshooting.
• Design and build AI-driven workflows and agents that automate repetitive data engineering work, such as table ingestion, source profiling, data parity checks, and release validation.
• Build and maintain MCP (Model Context Protocol) connections that let AI tools work safely with our data sources.
• Help define guardrails and best practices for responsible AI use, including read-only access, human review of AI-generated code, and protection of sensitive data.
• Mentor and coach junior data engineers, fostering a culture of continuous learning and improvement.

If you are ready to join our fast-paced company, apply below!

We are an Equal Opportunity Employer. All qualified applicants for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity, ancestry, age, or national origin will be considered. No qualified applicants will be discriminated against on the basis of disability or protected veteran status.