Data Engineer II

Reed Elsevier Philippines; Philippines; Hybrid; PHP 1,200,000 - 2,400,000; Full time

Benefits offered by this job

Hybrid work setup

IT equipment provided

HMO coverage for you and dependents

Retirement package with company match

Life and accident insurance

Paid time off 24 days + 6 days after 5

Merit-based incentives

Training and certifications

Job summary

Reed Elsevier Philippines is seeking a Data Engineer to design and build modern data platforms powering analytics, AI, and digital transformation initiatives. You will develop scalable, governed data foundations and collaborate with stakeholders, architects, engineers, analysts, and AI practitioners to turn fragmented data into trusted, high-value assets.

Based in Quezon City with a hybrid setup (1 day onsite per month), the role focuses on data pipelines, data lakes/warehouses, data quality and

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, Data Science, or a related field.
• 4+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, or similar roles.
• Strong proficiency in SQL and Python.
• Experience building ETL/ELT pipelines and modern data architectures.
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of data modeling, data warehousing, and data management principles.
• Experience integrating data from multiple systems and APIs.
• Knowledge of data governance, security, privacy, and quality management practices.
• Strong analytical, problem-solving, and communication skills.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data platforms.
• Build and optimize data lakes, warehouses, and modern cloud-based data architectures.
• Integrate data from enterprise systems, applications, APIs, documents, and operational platforms.
• Develop reusable data products that support reporting, analytics, machine learning, automation, and AI solutions.
• Implement data quality, governance, lineage, metadata, and monitoring frameworks.
• Support the development of intelligent applications through well-structured and AI-ready datasets.
• Collaborate with technical and business teams to translate requirements into scalable solutions.
• Champion best practices in data engineering, platform reliability, automation, and security.
• Contribute to the evolution of enterprise data and AI platforms.

Skills

SQL

Python

ETL/ELT pipelines

AWS

Azure

Google Cloud

Data modeling

Data warehousing

Data governance

APIs integration

Analytics

Communication

Education

Bachelor's degree

Tools

Power BI

Tableau

Job description

Join us and enjoy benefits designed to help you thrive:

• Flexible hybrid work setup (1 day/month onsite reporting)
• IT Equipment provided
• HMO coverage starting from Day 1 for you and FOUR FREE dependents
• Attractive retirement package with company matching
• Life and Accident Insurance starting Day 1
• 24 Annual PTOs, additional 6 once you reach your 5th year with us
• Competitive benefits with annual merit increase and incentives
• Continuous improvement for our employees (workshops, certification programs, learning sessions, etc.)

Work Arrangement:

• Set-Up: Hybrid (1/month onsite reporting)
• Schedule: Midshift 2:00 PM - 10:00 PM
• Location: UP AyalaLand Technohub, Commonwealth, Quezon City

Job Description:

We are seeking a Data Engineer to help design and build modern data platforms that power analytics, artificial intelligence, automation, business applications, and digital transformation initiatives.

You will play a critical role in creating scalable, governed, and reliable data foundations that enable organizations to make better decisions, develop intelligent solutions, and accelerate innovation. Working alongside business stakeholders, architects, software engineers, analysts, and AI practitioners, you will transform fragmented data into trusted, reusable, and high-value data assets. This role aligns with initiatives involving governed data foundations, AI-ready knowledge assets, analytics enablement, and enterprise platform integration.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data platforms.
• Build and optimize data lakes, warehouses, and modern cloud-based data architectures.
• Integrate data from enterprise systems, applications, APIs, documents, and operational platforms.
• Develop reusable data products that support reporting, analytics, machine learning, automation, and AI solutions.
• Implement data quality, governance, lineage, metadata, and monitoring frameworks.
• Support the development of intelligent applications through well-structured and AI-ready datasets.
• Collaborate with technical and business teams to translate requirements into scalable solutions.
• Champion best practices in data engineering, platform reliability, automation, and security.
• Contribute to the evolution of enterprise data and AI platforms.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, Data Science, or a related field.
• 4+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, or similar roles.
• Strong proficiency in SQL and Python.
• Experience building ETL/ELT pipelines and modern data architectures.
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of data modeling, data warehousing, and data management principles.
• Experience integrating data from multiple systems and APIs.
• Knowledge of data governance, security, privacy, and quality management practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with cloud-native services for data storage, orchestration, and analytics.
• Experience building enterprise data lakes, lakehouses, or knowledge repositories.
• Familiarity with business intelligence and analytics platforms such as Power BI or Tableau.
• Experience supporting AI, machine learning, generative AI, or intelligent automation initiatives.
• Knowledge of DevOps, CI/CD, Infrastructure-as-Code, and platform engineering practices.
• Experience working in large-scale transformation, analytics, technology, or innovation programs.