NCS Philippines, in partnership with Globe and part of the NCS Group, a leading Asia-Pacific technology services firm and subsidiary of the Singtel Group, is a workplace where people and innovation come together to create meaningful impact. 

Employees at NCS Philippines work on a wide range of projects across digital, data, cloud, platforms, and cybersecurity, supporting enterprises and government agencies in solving real-world challenges. With access to NCS’ regional network of over 15,000 professionals across 55 specialisations, teams gain valuable exposure to global best practices while contributing to local impact. 

The company fosters a culture rooted in collaboration, continuous learning, and growth. Employees are empowered to expand their capabilities, explore emerging technologies, and build solutions that go beyond technical delivery – creating tangible value for clients and communities. 
Through strong partnerships, a diverse talent base, and opportunities for regional collaboration, NCS Philippines enables their people to grow their careers while being part of something bigger: advancing communities through technology and shaping the future of digital innovation.



NCS Philippines Inc. 

<ul>
	<li>Provides expert knowledge of master data in support of Business, Operations, and Technology teams. </li>
	<li>Manages change control processes and systems related to Formula Control. </li>
	<li>Manages processes to maintain current and historical formulation and raw material information files. </li>
	<li>Develops standards, guidelines, and processes to consistently address master data issues such as data standards and data synchronization</li>
	<li>Develops procedures and processes in compliance with current identified and ISO standards while maintaining the integrity and security of the formulations.</li>
	<li>Provides expert knowledge of master data in support of Business, Operations, and Technology teams.</li>
	<li>Develops standards, guidelines, and processes to consistently address master data issues such as data standards and data synchronization.</li>
	<li>Supports in driving efforts for the adoption of the Data Governance policies, master data management principles and policies and their implementation, work closely with different teams to drive adoption, and overcome individual and organizational resistance to change.</li>
	<li>Contributes to research and efforts to understand and document how data should be best managed and used in the MDM based on laws and best practices</li>
	<li>Works with data owners when issues are escalated</li>
	<li>Evaluates escalated issues for potential solutions to resolve</li>
	<li>Determines if an unresolved issue requires further escalation</li>
	<li>Works with all resources to ensure that business rules are implemented properly to support business needs</li>
	<li>Other job-related activities that may be assigned from time to time.</li>
</ul>

Data Engineer {Data Governance}

We are seeking a Data Architect to design, govern, and evolve our enterprise data landscape with a strong focus on modern data lakehouse architecture. This role is responsible for building scalable, secure, and analytics-ready data platforms that support reporting, advanced analytics, and AI/ML initiatives. The ideal candidate combines strategic architectural thinking with deep hands-on experience in cloud-based data ecosystems.

Key Responsibilities 
 
Data Architecture &amp; Platform Design

Define and own the enterprise data architecture and target-state data landscape

Design and implement data lakehouse architectures supporting structured and unstructured data

Lead modernization from legacy data warehouses to lakehouse-based platforms

Establish architecture standards, patterns, and best practices

Data Integration &amp; Processing

Architect batch and real-time data ingestion pipelines

Design scalable data processing frameworks using distributed compute

Integrate data from transactional systems, APIs, and third-party sources

Ensure data reliability, performance, and cost efficiency

 
Governance, Quality &amp; Security

Define and enforce data governance, quality, and lineage standards

Architect secure data access models including role-based access control

Ensure data privacy and regulatory compliance through design

Implement metadata management and auditing capabilities

 
Analytics Enablement

Enable BI, analytics, and AI/ML workloads through optimized data models

Support self-service analytics and standardized semantic layers

Partner with data engineers, analysts, and business stakeholders

 
Technical Leadership

Provide architectural guidance and design reviews

Mentor data engineers and technical teams

Translate business requirements into scalable data solutions

Data Architect  [Data Lakehouse]

We are seeking a Senior Data Architect to design, govern, and evolve our enterprise data landscape with a strong focus on modern data lakehouse architecture. This role is responsible for building scalable, secure, and analytics-ready data platforms that support reporting, advanced analytics, and AI/ML initiatives. The ideal candidate combines strategic architectural thinking with deep hands-on experience in cloud-based data ecosystems.

Key ResponsibilitiesData Architecture &amp; Platform Design

Define and own the enterprise data architecture and target-state data landscape

Design and implement data lakehouse architectures supporting structured and unstructured data

Lead modernization from legacy data warehouses to lakehouse-based platforms

Establish architecture standards, patterns, and best practices 
 

Data Integration &amp; Processing

Architect batch and real-time data ingestion pipelines

Design scalable data processing frameworks using distributed compute

Integrate data from transactional systems, APIs, and third-party sources

Ensure data reliability, performance, and cost efficiency

 
Governance, Quality &amp; Security

Define and enforce data governance, quality, and lineage standards

Architect secure data access models including role-based access control

Ensure data privacy and regulatory compliance through design

Implement metadata management and auditing capabilities

 
Analytics Enablement

Enable BI, analytics, and AI/ML workloads through optimized data models

Support self-service analytics and standardized semantic layers

Partner with data engineers, analysts, and business stakeholders

 
Technical Leadership

Provide architectural guidance and design reviews

Mentor data engineers and technical teams

Translate business requirements into scalable data solutions

Data Architect  {Data Landscape & Lakehouse}

General Responsibilities:

The Data Engineer will focus on using various methods to design and implement an overall data infrastructure that will support current and future business needs. The data engineer is also tasked in creating data pipelines that transform raw data for analytical and operational processes.

Duties and Responsibilities:

-Design and build scalable big data infrastructure and solutions, leveraging available cloud resources 
-Design, create and maintain ETL processes and data pipelines for functions such as but not limited to reporting and machine learning 
-Collaborate with different cross functional teams to determine and satisfy business data requirements taking into account various technology stacks 
-Optimize and automate existing current business processes and procedures 
-Create and present ad hoc reports to key stakeholders

Data Engineer

NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group. 
 
Duties &amp; Responsibilities:

<ul>
	<li>Develops automated data pipelines based on recommended solution by Data Engineering Lead using official ETL tools determined by Data Engineering Head</li>
	<li>Creates automated data pipeline design documentation, Source-to-Target spreadsheets, and technical design specifications.</li>
	<li>Provides technical expertise, troubleshoots, guides and supports during design, development, testing, production and post-production.</li>
	<li>Understands the source system, captures and documents business rules.</li>
	<li>Analyzes and proposes changes to maximize code reusability and maintain business value.</li>
	<li>Develops, implements and maintains highly efficient and scalable automated data pipeline processes.</li>
	<li>Provides expert technical knowledge and solutions pertaining to Data integration.</li>
	<li>Identify opportunities to optimize the automated data pipeline including environment setup, implement monitoring, quality and validation processes to ensure data accuracy and integrity.</li>
	<li>Provides inputs into data governance organization to drive the data governance charter.</li>
	<li>Ensures compliance to internal standards and guidelines.</li>
	<li>Conducts unit testing and component integration testing for solutions developed</li>
	<li>Reviews business and technical requirements and ensures the data integration platform meets requirements.</li>
	<li>Applies industry best practices for automated data pipeline design and development.</li>
	<li>Implementation of an end-to-end complex automated data pipeline system using common Big Data Tools such as (but not limited to) Apache Spark, Talend, Kafka, Airflow, NiFi i and Hadoop Tools.</li>
	<li>Implements monitoring and measurement of data quality as defined by business rules.</li>
	<li>Ensures adherence to architectural governance standards and practices.</li>
	<li>Develops best practices, standards of excellence, and guidelines for programming teams.</li>
	<li>Ensures compliance to the DevSecOps practice.</li>
	<li>Conducts System Testing - execute job flows, investigate system defects, resolve defects and document results</li>
	<li>Provides a level of effort estimates for new initiatives and change controls in order for projects to be evaluated, budgeted and tracked for success.</li>
</ul>

Sr. Data Engineer

NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.

General Responsibilities:

The Lead Data Engineer is responsible for designing, developing, and optimizing data infrastructure to ensure reliable pipelines, scalable architecture, and high-quality data for analytics and business needs. The role includes leading a team of data engineers, collaborating with cross-functional stakeholders, and implementing best practices in data transformation, validation, governance, and cloud-based solutions.

Duties &amp; Responsibilities:

<ul>
	<li>Lead and mentor a team of data engineers, fostering collaboration, innovation, and continuous improvement.</li>
	<li>Define and enforce data engineering standards, coding practices, and architectural guidelines.</li>
	<li>Partner with data scientists, analysts, and business stakeholders to translate requirements into scalable solutions.</li>
	<li>Design and maintain high-performance ETL/ELT pipelines and workflows.</li>
	<li>Build and optimize data lake, data warehouse, and streaming data solutions.</li>
	<li>Ensure systems support structured, semi-structured, and unstructured data sources.</li>
	<li>Develop data transformation and preparation processes to deliver clean, reliable, analytics-ready datasets.</li>
	<li>Implement validation, anomaly detection, and automated quality checks to ensure accuracy and consistency.</li>
	<li>Define and execute data remediation strategies to resolve issues with minimal business disruption.</li>
	<li>Implement and manage cloud-based data platforms (AWS, Azure, or GCP).</li>
	<li>Apply modern frameworks (e.g., Spark, Kafka, Airflow, DBT) for efficient data processing.</li>
	<li>Oversee data modeling, schema design, and database optimization (SQL/NoSQL).</li>
	<li>Ensure accuracy, consistency, and availability of data across platforms.</li>
	<li>Implement governance, lineage, validation frameworks, and security best practices.</li>
	<li>Monitor, troubleshoot, and optimize pipelines to meet SLAs and performance benchmarks.</li>
	<li>Stay current with emerging data engineering and analytics technologies.</li>
	<li>Recommend improvements to systems, tools, and processes to enhance scalability, reliability, and quality.</li>
	<li>Other job-related activities that may be assigned from time to time</li>
</ul>

Lead Data Engineer

Company Overview 
 
NCS is a leading AI Tech Services company. With a 15,000-strong team across the Asia Pacific, NCS scales its platforms and capabilities to provide clients with greater agility and AI expertise across a range of industries. Embracing a strong ecosystem of global partners, NCS transforms technology services delivery combining AI with digital resilience to drive real business impact. NCS is a subsidiary of the Singtel Group.

General Responsibilities:

The Data Engineer will be responsible for designing, building, and maintaining robust data infrastructure and pipelines that support current and future business needs. This includes transforming raw data into actionable insights through scalable and secure pipelines, managing data assets effectively, and enabling seamless access to data for analytical and operational processes. The Data Engineer will collaborate with cross-functional teams to address data requirements, optimize workflows, and deliver impactful solutions through automation, visualization, and reporting.

BI and Data Engineer

Job Specifications

<ul>
	<li>Education – At least graduate with a Bachelor’s or Master's Degree in IT, Computer Science, Engineering, or any related course.</li>
	<li>Related Work Experience – at least 5 years of experience in data engineering, data analytics, or related fields.</li>
	<li>Proficiency in Python and Java, with experience in other programming languages as a plus.</li>
	<li>Hands-on experience with data manipulation tools (e.g., pandas, dplyr, or Spark).</li>
	<li>Proficiency in Extract, Transform, and Load (ETL) processes for efficient data pipeline management.</li>
	<li>Expertise in both SQL and NoSQL query languages for database interaction and management.</li>
	<li>Experience with big data storage and processing solutions, such as MongoDB, Spark, Hive, Snowflake, Redshift, or similar technologies.</li>
	<li>Experience with cloud-based or server-based data processing environments (e.g., AWS, Azure, GCP).</li>
	<li>With experience in Apache Nifi (nice to have)</li>
</ul>

Knowledge – Knowledgeable in the following:

<ul>
	<li>Comprehensive understanding of data manipulation tools such as pandas, dplyr, and Spark.</li>
	<li>In-depth knowledge of big data frameworks and tools like Apache Spark and Hadoop.</li>
	<li>Familiarity with data warehousing services like AWS Redshift, Snowflake, or similar solutions.</li>
	<li>Proficiency in AWS Cloud Services, particularly AWS Glue and AWS Lake Formation.</li>
	<li>Familiarity with business intelligence tools such as Tableau, Power BI, QuickSight, or Google Data Studio.</li>
	<li>Awareness of data visualization libraries and packages like Dash, Plotly, Matplotlib, ggplot, and Folium.</li>
	<li>Understanding of machine learning libraries and tools is a plus.</li>
	<li>Knowledge of data governance, quality control, and security best practices.</li>
	<li>Skills</li>
	<li>Problem-Solving: Ability to address technical challenges and deliver efficient data solutions.</li>
	<li>Communication: Clear and concise communication skills for collaborating with team members and stakeholders.</li>
	<li>Collaboration: Ability to work effectively within a team environment to achieve shared goals.</li>
	<li>Time Management: Capacity to manage tasks and meet deadlines in a structured and timely manner.</li>
	<li>Attention to Detail: Careful and accurate handling of data to ensure quality and integrity.</li>
	<li>Client-Focus: Ability to understand business needs and align data solutions to support decision-making and strategic objectives.</li>
	<li>Adaptability: Flexible and open to learning new tools, technologies, and processes in a rapidly changing environment.</li>
</ul>

Data Engineer {Python , SQL}

General Responsibilities:

The Data Engineer will focus on using various methods to design and implement an overall data infrastructure that will support current and future business needs. The data engineer is also tasked in creating data pipelines that transform raw data for analytical and operational processes.

Duties and Responsibilities:

-Design and build scalable big data infrastructure and solutions, leveraging available cloud resources 
-Design, create and maintain ETL processes and data pipelines for functions such as but not limited to reporting and machine learning 
-Collaborate with different cross functional teams to determine and satisfy business data requirements taking into account various technology stacks 
-Optimize and automate existing current business processes and procedures 
-Create and present ad hoc reports to key stakeholders

Data Engineer {Python & SQL}

The Data Engineer will focus on using various methods to design and implement an overall data infrastructure that will support current and future business needs. The data engineer is also tasked in creating data pipelines that transform raw data for analytical and operational processes. 
 
Duties and Responsibilities: 
 
-Design and build scalable big data infrastructure and solutions, leveraging available cloud resources 
-Design, create and maintain ETL processes and data pipelines for functions such as but not limited to reporting and machine learning 
-Collaborate with different cross functional teams to determine and satisfy business data requirements taking into account various technology stacks 
-Optimize and automate existing current business processes and procedures 
-Create and present ad hoc reports to key stakeholders

Data Engineer {Python, SQL and ETL}

Data Engineer {Java, Python, SQL}

<ul>
	<li>Execute performance tuning activities for model serving infrastructure to maintain optimal latency and throughput.</li>
	<li>Conduct post-deployment validation checks to ensure model prediction stability, API responsiveness, and overall service quality.</li>
	<li>Support the enhancement of operational pipelines, including CI/CD workflows, configuration templates, and automated monitoring scripts.</li>
	<li>Participate in service reliability reviews to improve platform uptime, incident response processes, and operational readiness.</li>
	<li>Coordinate closely with DevOps and Platform Engineering to address infrastructure-level concerns related to model hosting and deployment.</li>
	<li>Assist in the rollout of platform-level improvements, including model registry enhancements, container optimization, and new monitoring tools.</li>
</ul>

Machine Learning Operations Specialist {Data Engineer} With background on Cloud

<ul>
	<li>What you'll be doing</li>
	<li>Lead the product strategy and roadmap for NCS Philippines' cloud and security product suite</li>
	<li>Gather and analyse market and customer insights to identify growth opportunities and inform product development</li>
	<li>Work cross-functionally with sales, delivery and engineering teams to shape the product vision and translate it into tangible solutions</li>
	<li>Manage the full product lifecycle, from ideation and prioritisation to launch and continuous improvement</li>
	<li>Drive product marketing and positioning to effectively communicate the value proposition to customers</li>
	<li>Monitor product performance and market trends to continuously optimise the product portfolio</li>
	<li>Build and lead a high-performing product management team</li>
</ul>

Product Director

Machine Learning Specialist {LLM}

General Responsibilities:

The Automation Engineer is responsible for developing and implementing quality assurance standards and measures within the project. Writes test plans, creating and executing both functional and automated tests, tracking defects and fixes, and reporting the progress of each.

Duties and Responsibilities:

Design/Development:

-Supports existing Test Automation Suite by conducting timely analysis and application of fixes.

-Maintains and expands Test Automation Suite.

-Designs and develops automated test scripts from Functional and Technical designs.

-Participates in the selection of automated test development tools.

-Reviews and understand Business Requirement, Functional, and Technical Design documents and come up with a Test Plan

-Performs project tasks and solve problems independently

Design/Development:

-Develops and/or maintains automated test plans and cases.

-Maintains documentation of test results.

Testing:

-Executes test cases and test scripts.

-Conducts new feature testing, regression testing, and bug fix testing.

-Analyzes and identifies which tests should be automated and which are not feasible for automation.

-Participates in defect and customer issue resolution process

-Performs peer automated test code reviews and optimize test code execution

-Other job-related activities that may be assigned from time to time.

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