Cloud Data Engineer

NNIT

Philippines

On-site

PHP 900,000 - 1,200,000

Full time

3 days ago

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Job summary

NNIT is seeking a Data Engineer for its AI Center of Excellence in the Philippines to design, build, and maintain enterprise data platforms that enable AI, analytics, and digital transformation.

You will collaborate with solution architects, AI engineers, consultants, product owners, and business stakeholders across Europe, Asia, and other regions to design modern data platforms that power enterprise AI and advanced analytics.

Qualifications

Bachelor's degree in Computer Science or related field
4–7 years of Data Engineering or Software Engineering experience
Strong SQL and Python programming skills
Experience building enterprise data platforms and ETL/ELT pipelines
Experience with cloud-based data platforms and Agile methodologies

Responsibilities

Design and build enterprise data platforms and pipelines
Improve data quality, reliability, availability, and observability
Collaborate with AI engineers, architects, analysts, consultants, and business stakeholders
Support enterprise reporting, analytics, and AI initiatives
Contribute to data governance and platform modernization initiatives

Job description

Data Engineer

NNIT AI Center of Excellence

Type of contract: Full-time

Location(s): Philippines

Language(s): English

Mobility: N/A

Application Deadline:

About The Role

As a Data Engineer, you'll design, build, and maintain enterprise data platforms that enable Artificial Intelligence, analytics, and digital transformation. Working within NNIT's AI Center of Excellence, you'll develop scalable, trusted, and AI-ready data solutions that support business-critical applications across global organizations.

You’ll collaborate with solution architects, AI engineers, consultants, product owners, and business stakeholders across Europe, Asia, and other regions to design modern data platforms that power enterprise AI and advanced analytics.

Success in this role requires strong data engineering fundamentals, systems thinking, and the ability to transform complex business requirements into scalable, high-quality data solutions that enable informed decision-making and AI innovation.

What You’ll Do

Build Data Platforms

Design and develop enterprise data pipelines using ETL/ELT frameworks.
Build scalable data lakes, lakehouses, and cloud-native data platforms.
Develop semantic models and AI-ready datasets for analytics and AI workloads.
Integrate data from enterprise applications, cloud platforms, APIs, and external data sources.
Design scalable, secure, and maintainable data architectures.

Engineer for Scale

Improve data quality, reliability, availability, and observability.
Optimize data pipelines for scalability, performance, and cost efficiency.
Apply modern data engineering, testing, and DevOps practices.
Build reusable frameworks, templates, and engineering standards.
Support enterprise data governance and platform modernization initiatives.

Partner with Stakeholders

Translate business requirements into scalable data solutions.
Collaborate with AI engineers, architects, analysts, consultants, and business stakeholders.
Support enterprise reporting, analytics, and AI initiatives.
Recommend improvements to data architecture, engineering practices, and platform capabilities.
Share knowledge and contribute to the growth of the AI Center of Excellence.

What Success Looks Like

Success in this role means you:

Deliver scalable and reliable enterprise data platforms.
Improve data quality, accessibility, and operational efficiency.
Enable AI-ready data for analytics and intelligent applications.
Contribute reusable engineering assets and best practices.
Support the continued growth and technical maturity of NNIT's AI Center of Excellence.

What You’ll Bring

We’re looking for engineers who combine technical expertise with business understanding, collaboration, and continuous learning.

Education

Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field.

Professional Experience

4–7 years of Data Engineering or Software Engineering experience.
Strong SQL and Python programming skills.
Experience building enterprise data platforms and ETL/ELT pipelines.
Experience working with cloud-based data platforms.
Experience delivering solutions using Agile methodologies.
Experience working within consulting, enterprise IT, or global delivery organizations is highly desirable.

Core Competencies

Strong analytical and systems thinking.
Solid data engineering fundamentals.
Ability to translate business needs into scalable data solutions.
Excellent written and verbal English communication skills.
Ability to work effectively with technical and non-technical stakeholders.
Ownership, accountability, and commitment to continuous learning.

Technologies You’ll Use

You’ll work with modern cloud data platforms and engineering tools that enable enterprise analytics, reporting, and Artificial Intelligence. While experience with every technology isn’t required, we’re looking for engineers with a strong technical foundation and the ability to learn and adopt modern data technologies.

Programming

Python
SQL

Data Platforms

Microsoft Fabric
Azure Data Factory
Databricks
Snowflake
Lakehouse Architecture
Delta Lake
Data Build Tool (DBT) (preferred)

Cloud & Engineering

Microsoft Azure
REST APIs
Git
Docker
CI/CD

Working in a Global Delivery Environment

At NNIT, you’ll work as part of One Global Team, collaborating directly with architects, consultants, AI engineers, analysts, and business stakeholders across Europe, Asia, and other regions. You’ll contribute throughout the data solution lifecycle—from architecture and engineering to deployment and continuous improvement.

Experience In The Following Environments Is Preferred

Global consulting firms.
Enterprise technology organizations.
Global Capability Centers (GCCs).
Shared Services organizations.
Multinational delivery teams operating across multiple countries and time zones.
Customer-facing or cross-functional project environments.

Industry Experience

Many of our customers operate in highly regulated industries where trusted data, security, compliance, and governance are business-critical. Exposure to enterprise data governance and compliance frameworks such as GxP, CSV, GDPR, HIPAA, ISO 27001, or similar standards is beneficial but not required.

Experience supporting one or more of the following industries is advantageous:

Life Sciences
Pharmaceuticals
Biotechnology
Healthcare
Medical Devices
Banking & Financial Services
Insurance
Manufacturing

Your Background

This role is well suited for professionals who have built enterprise data platforms while working closely with business stakeholders and cross-functional delivery teams.

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