Senior Data Engineer: Scalable Pipelines & Architecture

Foley

Philippines

Remote

PHP 7,402,837 - 11,104,255

Full time

14 days+

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Job summary

Foley is seeking a Senior Data Engineer to design, build, and scale data systems that power our operations and growth. You will develop reliable data pipelines, contribute to enterprise data architecture, and improve data modeling, governance, and access across the organization.

This hands-on role requires solving real technical problems, delivering production‑quality data solutions, and partnering with Engineering, Product, Analytics, and business stakeholders to ensure data is scalable,

Qualifications

  • Strong experience building and maintaining ETL/ELT pipelines in production environments.
  • Experience with batch and streaming / CDC / event-driven data patterns.
  • Ability to design scalable warehouse schemas and data models within a layered architecture.
  • Strong Python, SQL, and cloud-based data platforms experience.
  • Experience with AWS data services (Redshift, Glue, Lambda, S3, EventBridge).
  • Strong software engineering fundamentals: reliability, testing, maintainability.

Responsibilities

  • Design, build, and maintain scalable data pipelines across databases, vendor systems, and data warehouse.
  • Support batch and event-driven workflows; improve pipeline reliability and observability.
  • Build and maintain data warehouse schemas and transformation layers for analytics.
  • Partner with Engineering, Product, Analytics to translate requirements into data solutions.
  • Identify opportunities to improve data workflows and adopt AI-enabled tooling where appropriate.

Skills

ETL/ELT pipelines
Python
SQL
AWS data services
Data modeling
Data governance

Tools

Redshift
Glue
Lambda
S3
EventBridge

Job description

Foley is seeking a Senior Data Engineer to design, build, and scale data systems that power our operations and growth. You will develop reliable data pipelines, contribute to enterprise data architecture, and improve data modeling, governance, and access across the organization.

This hands-on role requires solving real technical problems, delivering production‑quality data solutions, and partnering with Engineering, Product, Analytics, and business stakeholders to ensure data is scalable,

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