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Data Engineer

Octal Philippines • IT Outsourcing & Dedicated Teams • Recruiting & Staffing • Bachelor's Degree • Python • SQL • Tableau • Power BI • ETL/ELT • Looker • 1 year ago

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Location

In office (Quezon City, Taguig)

Employment

Full-Time

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Jun 25, 2025. Octal Philippines scores C on the Alion truth index.

Overview

Company

Impact

Profile match

Octal Philippines

Octal Philippines is a technology outsourcing and staffing company based in Manila that supplies engineers, support specialists and back-office staff to clients in North America, Europe and Australia. Its work covers software development, quality assurance, technical support, data processing and customer operations, delivered from its own facilities in the Philippines under the offshore delivery model the country built its services industry on. It advertises client vacancies under its own name rather than the end employer's, which is why its board carries roles spanning several unrelated industries at once.

octalphilippines.com • HQ: Manila, Philippines • IT Outsourcing & Dedicated Teams • Business Process Outsourcing (BPO) • Recruiting & Staffing • 201-500 employees

Requirements:

Experience: Proven experience as a Data Engineer or similar role with a focus on data pipelines, cloud infrastructure, and reporting.
Technical Skills: Strong understanding of data engineering concepts, tools, and technologies (e.g., SQL, Python, ETL tools, cloud platforms).
Cloud Platforms: Experience with major cloud platforms (e.g., AWS, Azure, GCP) and their data-related services (e.g., data warehouses such as BigQuery/Redshift, data lakes, data pipelines).
Data Modeling: Proficiency in data modeling techniques (e.g., dimensional, normalized) and data warehouse design.
Reporting and Visualization: Expertise in using reporting and visualization tools (e.g., Looker, Power BI, Tableau) to create interactive dashboards.
Problem-Solving: Ability to troubleshoot complex data-related issues and find innovative solutions.
Communication: Excellent communication skills to collaborate effectively with cross-functional teams.
Certifications: Preferred certifications (e.g., AWS Certified Data Engineer, Azure Certified Data Engineer, GCP Certified Professional Data Engineer).

Requirements

Additional Skills (Preferred):

Experience with data warehousing and data lake technologies (e.g., Google BigQuery, Amazon Redshift, Snowflake, Databricks)
Knowledge of data analytics and machine learning concepts
Familiarity with data governance and compliance frameworks (e.g., HIPAA, GDPR, CCPA)

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