Data Analytics

• Spearhead the design and execution of end-to-end data analytics strategies.
• Develop and manage automated data pipelines and ETL workflows.
• Perform data cleaning, preprocessing, and validation to maintain high data accuracy and integrity.
• Utilize advanced statistical and data mining techniques to analyze extensive healthcare datasets.
• Build and maintain interactive dashboards with user-friendly visualizations tailored for non-technical stakeholders.
• Deliver in-depth analytics to support clinical research and quality improvement projects, especially in areas like chronic disease management (e.g., diabetes, kidney disease, asthma).
• Create predictive models and deploy machine learning solutions, including large language models (LLMs).
• Collaborate with clinical teams to integrate Patient-Reported Outcome Measures (PROMs) into existing care processes.
• Work closely with GTO and AIO teams to improve data visibility and accessibility.
• Design and apply LLM-based solutions to streamline and optimize patient care pathways.

Data Quality & Monitoring

• Conduct regular validation to ensure the integrity and consistency of datasets.
• Detect and interpret key trends, patterns, and insights from healthcare data.
• Establish and maintain robust data quality assurance and validation protocols.
• Generate and present clear, data-driven reports and visualizations to stakeholders.
• Ensure all data visualizations are user-centric and accessible to non-technical users.
• Liaise with cross-functional teams to gather and address their specific data requirements.

Data Governance & Protection

• Implement stringent data security policies and access controls.
• Supervise data standardization and quality management initiatives.
• Ensure adherence to data privacy laws such as PDPA and HBRA.
• Develop secure protocols for safe data exchange and collaborative access.
• Promote ethical AI usage and ensure responsible deployment of LLM technologies.

Key Requirements

• Bachelor’s degree in a quantitative field (e.g., Computer Science, Data Analytics, Statistics)
• Minimum of 2 years’ experience in healthcare analytics or a similar field.
• Strong programming skills in Python, R, and SQL.
• Hands-on experience with data visualization platforms such as Tableau, Power BI, or TIBCO Spotfire.
• Proficiency with cloud analytics environments, especially Databricks.
• Solid foundation in statistical methods, including predictive modeling, A/B testing, and time-series analysis.
• Skilled in deploying and fine-tuning AI/ML models, including LLMs, within healthcare contexts.
• Experience working with cloud providers, particularly AWS.
• Familiarity with container technologies like Docker and Kubernetes.
• Experience using modern web frameworks such as Streamlit, NextJS, and TypeScript.
• Proficient in REST API development using frameworks like FastAPI.
• Understanding of database design, with hands-on experience using tools like SQLAlchemy.
• Capable of working with large and complex datasets.
• Proficient in using Git for version control and collaborative coding.
• Strong grasp of CI/CD pipelines and DevSecOps best practices.
• Knowledge of medical terminology and healthcare IT systems.
• Demonstrated ability to manage stakeholders and drive successful project outcomes.
• Excellent analytical thinking and problem-solving capabilities.
• Effective communicator with strong presentation, writing, and interpersonal skills.
• Highly detail-oriented, with a commitment to accurate data handling and analysis.
• Able to convert business challenges into technical data solutions.
• Team-oriented, proactive, and capable of thriving under time constraints.
• Comfortable working both independently and collaboratively in dynamic environments.

To apply, please visit www.gmprecruit.com

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA License: 11C3793 | EA Personnel: Bautista Gia Grace De Guzman | Registration No: R23111973

Role Overview:

We are looking for a Data Engineer to support large-scale government and defence-related data projects, focusing on building secure, scalable, and reliable data platforms and ETL/ELT pipelines across cloud and enterprise environments.

Job Responsibilities:

Data Engineering & Platform Development

• Design and develop scalable and reliable data pipelines.
• Build enterprise data platforms, including data warehouses, data lakes, and lakehouses.
• Implement cloud, hybrid, and on-premises data architectures aligned with enterprise standards.

ETL/ELT & Data Integration

• Lead ETL/ELT pipeline development, with Talend as a highly preferred platform.
• Integrate structured, semi-structured, and unstructured data sources.
• Implement and maintain data quality, validation, and error-handling frameworks.

Data Management & Governance

• Design and manage data storage solutions with a strong focus on object storage, data quality, and data governance.
• Implement and maintain data lifecycle management and cost-optimisation strategies.
• Ensure data lineage, traceability, and auditability.

Analytics & BI Enablement

• Engineer analytics-ready data models for reporting and self-service analytics.
• Enable BI dashboards, reports, and analytics through performant and governed data pipelines.

Security & Compliance

• Ensure compliance with government security and privacy requirements.
• Implement and maintain encryption, access controls, secure data handling practices, and system security policies.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum 3 years of experience in enterprise data engineering roles.
• Strong hands-on data engineering experience.
• Strong SQL and Python skills.
• Experience with ETL/ELT tools, with Talend highly preferred.
• Experience with data warehouses, data lakehouses, data lakes, and object storage systems.
• Qlik Sense Enterprise integration experience is highly preferred.
• Prior CAT 1 / G50 security clearance is required.
• Previous experience delivering MINDEF projects is required.

1. Position Summary

We are looking for a Data Engineer to join our team and contribute to a major project within the semiconductor manufacturing domain. The role involves designing and implementing data pipelines, managing Oracle-based data environments, and supporting end-to-end BI processes — from data ingestion to visualization. This position is based on-site at our partner’s advanced manufacturing facility, offering hands-on exposure to large-scale industrial data systems.

2. Key Responsibilities

• Design, develop, and maintain Python-based applications and APIs to extract, transform, and deliver data in JSON format.
• Design and create robust data models to support efficient querying and reporting.
• Define relationships, hierarchies, and calculated columns/measures that align with business logic.
• Design, develop, and maintain data pipelines and ETL workflows for manufacturing data (ERP, MES, SPC, FDC, etc.).
• Implement and optimize database logic, including stored procedures, functions, and PL/SQL scripts.
• Build and manage staging schemas, data validation processes, and data transformation logic.
• Develop and maintain data marts and dimensional models to support analytics and reporting.
• Collaborate with BI developers and analysts to deliver Power BI dashboards, KPI reports, and visual analytics.
• Ensure data accuracy, consistency, and completeness across multiple source systems.
• Support data governance, documentation, and performance tuning efforts.
• Partner with internal and external stakeholders to ensure timely and high-quality data delivery for business use.
• Perform any ad-hoc duties assigned by the Company as and when required.

3. Qualifications& Skills

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Minimum 3 years of experience in data engineering, data integration, or BI development.
• Proficient in Python programming, specifically for data extraction, API development, and JSON data manipulation.
• Strong understanding of data warehousing concepts, schema design, and ETL best practices.
• Solid working experience with relational databases (e.g. Oracle, SQL Server, MySQL, PostgreSQL), including stored procedures and query optimization.
• Proficient with ETL tools such as Pentaho Kettle, Informatica, Talend, or similar.
• Experience developing reports and dashboards in Power BI (or Tableau/Qlik).
• Familiarity with SQL pipelines, data validation, and data replication tools.
• Strong analytical and problem-solving mindset with attention to data quality and performance.
• Ability to work collaboratively with business, IT, and engineering teams in fast-paced environments.
• Excellent documentation and communication skills.

4. Preferred /Additional

• Experience in semiconductor or manufacturing systems (ERP, MES, SPC, FDC) preferred.
• Exposure to data replication frameworks (Oracle Golden Gate, SharePlex, AWS Glue) is an advantage.
• Experience developing custom Python applications/APIs for data extraction and familiarity with JSON data structures is highly preferred.
• Familiarity with cloud-based data warehouses (Snowflake, Redshift, Synapse) and Giga Report is a plus
• Knowledge of data governance frameworks, metadata management, and data security best practices.

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Responsibilities:

• Data Infrastructure: Build, implement, and maintain scalable data pipelines and storage architectures.
• Data Quality: Maintain strong data integrity by ensuring reliability, consistency, and accuracy across all data processes.
• Performance Optimization: Enhance system efficiency by tuning data processing workflows and improving large-scale performance.
• Process Improvement & Mentoring: Strengthen data engineering practices while providing guidance and support to junior engineers.
• Cross-Functional Collaboration: Partner with business analysts, data scientists, and backend teams to deliver timely and actionable data solutions.

Qualifications:

• 5+ years’ experience in data engineering or backend roles, with strong programming skills in Python or Java/Scala.
• Hands-on experience with big data tools: Spark, Flink, Kafka, Airflow, and cloud platforms (AWS, GCP, Azure); proficient in SQL.
• Skilled in designing and maintaining data models, warehouses, and ETL/ELT pipelines for scalable, reliable systems.
• Knowledgeable in data quality, governance, security, and compliance best practices.

We regret only shortlisted candidates will be contacted. All applications will be handled confidentially. By submitting your application, you agree to the collection, use, retention, and disclosure of your personal information to prospective employers.

Wecruit Pte Ltd
EA License No: 20C0270
EA Personnel: Nyon Hock Sen (Aden)
EA Personnel Reg No: R24124070

About Company

Our client is a leading public sector organization driving initiatives at the intersection of healthcare, research, and data innovation. As part of a growing national effort to strengthen biomedical research capabilities, they are seeking an experienced leader to shape how health and biomedical data are prepared for future scientific and AI applications.

Roles & Responsibilities

• Lead programmes that improve the quality, usability, and accessibility of biomedical datasets to support research and innovation initiatives.

• Bring together clinicians, researchers, data specialists, and institutional stakeholders to align on approaches to data interpretation, standardization, and readiness.

• Develop frameworks and operating models that enable teams to deliver complex data initiatives effectively across organizational boundaries.

• Identify opportunities to strengthen data practices through the adoption of appropriate methodologies, technologies, and industry best practices.

• Act as a trusted advisor to stakeholders, balancing scientific objectives, operational realities, and governance considerations to drive successful outcomes.
  

Key Requirements

• Degree in Bioinformatics, Health/Medical Informatics, Data Science, Medicine, or a related discipline.

• At least 10 years of relevant experience in healthcare, biomedical research, health informatics, bioinformatics, or other data-driven environments.

• Experience working with healthcare institutions, research organizations, or stakeholders responsible for managing and governing health-related data.

• Familiarity with health data standards, data governance principles, and the practical challenges of preparing complex datasets for research use.

• Strong stakeholder management and communication skills, with a proven ability to lead cross-functional initiatives and influence outcomes in complex environments.

• Advanced qualifications (e.g. PhD) in a relevant discipline would be advantageous.
  

Application Process

To apply, please send your updated resume to Sean Wong (Registration ID No. R1441040) at sean.wong@cornerstoneglobalpartners.com with the job title or apply through the application link. Only shortlisted candidates will be notified. Information provided in this advertisement is for recruitment purposes only.

Cornerstone Global Partners (EA Licence Number: 19C9859) is an affirmative equal-opportunity employer and recruitment firm. We evaluate qualified applicants without regard to race, colour, religion, creed, gender identity, marital status, national origin, veteran status, disability, or any other protected class. with the job title or swiftly or apply through Jobstreet. Only shortlisted candidates will be notified. Information provided in this advertisement is for recruitment purposes only.

• Design, develop, and maintain scalable data pipelines and data processing frameworks.
• Build ETL/ELT solutions to ingest, transform and process structured and unstructured data.
• Develop high-performance data workflows using Python, Spark and distributed computing technologies.
• Implement data models, data lakes, warehouses and Lakehouse architecture.
• Develop and support data pipelines powering AI/ML models and analytics solutions.
• Partner with Data Scientists to produce machine learning models.
• Build feature engineering pipelines and reusable ML datasets.
• Implement MLOps practices, including model deployment, monitoring and lifecycle management.

Skills/Requirement -

• Strong hands-on experience in Data Engineering.
• Hands-on experience building large-scale data pipelines.
• Strong programming experience with Python.
• Experience working with cloud-based data platforms.
• Exposure to AI/ML model lifecycle and MLOps practices.

Responsibilities

• Support the deployment and implementation of AI infrastructure and data centre projects.
• Coordinate project activities with customers, distributors, vendors, technology partners, and internal engineering teams.
• Assist in the design and implementation of AI computing solutions, including GPU servers, storage systems, networking equipment, and cooling infrastructure.
• Participate in customer meetings, technical discussions, and project planning activities.
• Prepare technical proposals, system architecture designs, deployment plans, and project documentation.
• Manage project schedules, milestones, deliverables, and progress reporting to ensure timely project execution.
• Coordinate and oversee Factory Acceptance Testing (FAT) and Site Acceptance Testing (SAT).
• Support installation, commissioning, troubleshooting, and maintenance of AI infrastructure solutions.
• Collaborate closely with global technology partners and OEMs to ensure successful project delivery and system integration.
• Ensure compliance with customer requirements, industry standards, and project specifications.
• Provide post-deployment technical support, issue resolution, and project follow-up to maintain customer satisfaction.

Requirement

• Min Diploma in Electrical Engineering, Mechanical Engineering, Computer Engineering, Information Technology, or related disciplines.
• Min 2 years of experience in project engineering, systems integration, data centres, IT infrastructure.
• Knowledge of servers, networking, storage systems, power distribution, cooling systems, or data centre infrastructure.
• Familiarity with AI computing platforms, GPU technologies, and high-performance computing environments will be an advantage.
• Require to travel locally and overseas when required.

To submit your application, please apply online to apply@rn-care.com or call +(65) 6513 5697 for private and confidential discussion.

Your interest will be treated with the strictest of confidence. We regret that only shortlisted candidates will be notified or contacted.

RN Care Pte. Ltd
EA License No: 17C8900

Executive Summary

Smart IMS Inc provides Digital technology & Cloud transformation services, Application & Infrastructure Management Services, Unified Communications, and Insurance implementation services to customers across the Americas, Europe, Middle East, and Asia-Pacific regions.

As the trusted technology and business partner of leading MNCs, including Global Investment Banks, Smart IMS is also a Microsoft Gold Certified Partner, Oracle Platinum Partner and AWS MSP Partner.

We currently have an opening for a Data Centre Cabling Coordinator role for our client in Singapore which is a leading global investment bank. The Cabling Coordinator is responsible for coordinating and managing structured cabling requests across the APAC region, covering data centres and network rooms. 

The role ensures timely delivery, standardisation, and compliance with cabling standards while supporting regional projects and operational requests, including after‑hours and weekend activities when required.

Key Responsibilities

• Act as the regional point of contact for APAC cabling requests (MACs, projects, refreshes).
• Coordinate cabling activities with local sites, vendors, and internal teams.
• Ensure cabling works comply with global standards, labelling conventions, and best practices.
• Review cabling designs, rack layouts, and pathways for feasibility and scalability.
• Track request status, manage schedules, and provide regular updates to stakeholders.
• Validate work completion, testing results, and documentation.
• Support weekend and after‑hours cabling activities for critical implementations.

Required Skills & Experience

• Experience coordinating structured cabling in data centres and network rooms.
• Strong knowledge of fibre and copper cabling standards and practices.
• Experience working across multiple countries/sites in APAC will be an advantage
• Strong coordination, communication, and documentation skills.

Working Conditions

• Regional APAC coverage with occasional weekend and after‑hours support as required.

Role Overview

We are seeking a Data Engineer to design, develop, and maintain scalable, secure, and reliable data platforms and pipelines that support business and operational needs. The successful candidate will work closely with stakeholders, engineers, and data stewards to deliver high-quality data products while ensuring strong governance, security, and operational excellence.

Key Responsibilities

Data Pipeline Development and Architecture

• Translate business and data requirements into technical specifications and scalable data solutions.

• Develop and maintain data products as part of a cross-functional data team.

• Design, build, and optimise data ingestion pipelines to collect, transform, integrate, and harmonise data from multiple source systems.

• Design, develop, test, and maintain reusable data models to support reporting, analytics, and operational use cases.

• Implement secure and efficient mechanisms for users and applications to access enterprise data assets.

• Evaluate and implement new technologies, tools, and processes to enhance data infrastructure capabilities and performance.

Data Quality, Testing and Validation

• Develop and implement data quality controls and validation processes to ensure data accuracy, completeness, and consistency.

• Design, execute, and maintain test cases for data pipelines, including functional, regression, and exploratory testing.

• Build and maintain automated testing frameworks to improve data reliability and reduce production defects.

• Perform data reconciliation and integrity testing to validate end-to-end data processing and transformation workflows.

• Support User Acceptance Testing (UAT) activities by working with stakeholders to validate business requirements and expected outcomes.

Operations, Governance and Continuous Improvement

• Monitor and maintain databases, ETL processes, and data platforms, including performance optimisation, troubleshooting, capacity planning, and operational support.

• Collaborate with technology teams and stakeholders to align infrastructure, security, and platform requirements.

• Support the implementation and enforcement of data governance policies, standards, and best practices.

• Maintain data catalogues, metadata repositories, and data lineage documentation.

• Implement data security controls, including access management, encryption, masking, and other data protection measures.

• Drive continuous improvements in CI/CD, DevOps, and Site Reliability Engineering (SRE) practices.

Requirements

Qualifications and Experience

• Bachelor's Degree in Computer Science, Software Engineering, Information Technology, or a related discipline.

• Strong understanding of system design principles, data structures and algorithms, data modelling, data access patterns, and data storage technologies.

• Experience designing, building, and maintaining batch and real-time data pipelines.

• Hands-on experience with workflow orchestration tools such as Apache Airflow and Azure Data Factory.

• Proficiency in Python, SQL, and Shell scripting.

• Experience working with cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform (GCP).

• Experience with Databricks.

• Experience implementing data quality frameworks, validation processes, and testing methodologies for data pipelines.

• Familiarity with automated testing approaches and integration within CI/CD environments.

• Experience with issue tracking and test management tools such as JIRA or equivalent platforms.

• Familiarity with CI/CD pipelines and DevOps practices.

• Experience using DevOps tools such as Docker, Git, and Terraform.

• Experience implementing solutions that support data security, data quality, and data governance requirements.

Preferred Experience

• Familiarity with government-sector data management, governance, infrastructure, and security frameworks.

• Experience in climate, weather, environmental, or geospatial data domains will be advantageous.

Additional Information

• Appointment level and remuneration will be commensurate with qualifications, skills, and relevant experience.

About the job   

• Acts as point-of contact for Input Operations processes  
• Act as secondary point of contact in the absence of team lead in managing E2E operational queries and deliverables  
• Act as the SPOC for all the queries/data investigations and managing the internal stakeholders on the assigned queries 

Responsibilities  

• 1st function IV - Input Validation level, Production flow, what kind of validation, overall flow of the production, how functions coordinate each other  
• Database management system - understanding; can see a broader picture of the function  
• Get data from different sources, data handling, data evaluation, data analytics  
• Data Production process, reports  
• what kind of output that needs to be impacted from the input approach  
• 60%/ 70% system knowledge; 40%/ 30% analytics  
• Focus on IV - should see a broader level, what can foresee/ view on data  
• In-house system/ execution system  
• Project implementation, research - getting input from RMS or different sources, data validatio

Our client is a well established data centre and IT infrastructure company that focuses on providing carrier-neutral data centre services, network connectivity, managed services and related technology solutions.

They are looking for a motivated Senior Data Centre Engineer to support the day-to-day operations and maintenance of mission-critical data centre infrastructure. In this role, you will be responsible for ensuring the reliable operation, maintenance, and optimisation of data centre facilities. This role provides technical leadership in managing critical M&E infrastructure, supports service delivery excellence, and ensures compliance with safety, operational, and regulatory standards.

Key Responsibilities

Data Centre Operations & Reliability

• Oversee day-to-day operations of critical infrastructure including power, cooling, fire suppression, and monitoring systems.
• Ensure high availability and resilience of all active and redundant systems.
• Lead response to alarms, incidents, and emergencies, performing root cause analysis and corrective actions.

Maintenance & Engineering

• Plan, supervise, and execute preventive and corrective maintenance activities.
• Review maintenance procedures and implement improvements to enhance system reliability and efficiency.
• Manage testing of backup systems (UPS, generators, switchgear, CRAC, etc.).

Technical Leadership

• Provide technical guidance and mentorship to junior engineers and technicians.
• Act as escalation point for complex technical issues.
• Support audits, certifications, and compliance initiatives (e.g. ISO, SS 564, Uptime).

Customer & Stakeholder Support

• Coordinate customer installations, move-ins, turn-ons, and infrastructure changes.
• Ensure contracted SLAs and KPIs are met or exceeded.
• Liaise with internal teams, vendors, and customers to support operational requirements.

Projects & Change Management

• Support data centre projects, upgrades, and capacity expansion works.
• Review technical designs, method statements, and risk assessments.
• Oversee contractors and ensure works are carried out safely and in accordance with standards.

Safety, Compliance & Reporting

• Ensure strict adherence to workplace safety, SOPs, and regulatory requirements.
• Prepare incident reports, operational logs, and performance reports.
• Participate in shift coverage and on-call rotation as required.

Requirements

• Willing to work 24/7 rotating shifts
• Willing to work at both locations
• At least 4-5 years of relevant experience for a data centre

Work Locations: Bedok/Woodlands (Rotation of location will be required)

Working Hours

Morning Shift: 8.30am - 8.30pm

Night Shift: 8.30pm - 8.30am

(Shifts will rotate every 2 weeks)

Shift pattern: work 3 days rest 3 days, work 2 days rest 2 days

Salary

Up to $5500

Benefits

AWS, Variable Bonus, Allowances, Flexi benefits, 21 days annual leave

Interested candidates kindly click APPLY NOW to submit your latest CV.

We regret that only shortlisted candidates will be notified.

Search Avenue Pte Ltd

EA License No.: 25C2695

EA Registration No.: R25157669 [Amanda Wee]

Company Overview

A-IT Software Services Pte Ltd, established in 1991 and headquartered in Singapore, specializes in development outsourcing with expertise in project management, system design, and development for consumer banking, credit cards, and loans. The company has a strong track record and regional presence in Malaysia.

Job Summary

You will analyze financial data using Python and analytics tools to deliver ad hoc insights and develop data analytics solutions that support business decision-making in financial institutions.

Responsibilities

• Analyze financial data using Python to generate actionable insights for business stakeholders
• Develop, build, and maintain data analytics solutions to support ongoing business needs
• Use analytics platforms and tools effectively to extract, transform, and visualize data for reporting and decision support
• Provide ad hoc data analysis and insights to address specific business questions and challenges

Other Information

This job advertisement is posted by: Tan Geok Khim (Deng Yuqin) (R22107857) A-IT Software Services Pte Ltd

• EA License No: 24C2345

• “By submitting your application for this position, you consent to the collection, use, and disclosure of your personal data by A-IT Software Services and its recruitment partners, including Employment and Employability Institute Pte Ltd, for the purpose of i) employment facilitation and ii) data and statistical analysis. You may find out more information on the PDPA policies at [A-IT Software Services PDPA website] and [https: //www.e2i.com.sg/pdpa/].”

Department Overview:

The Intl AI CoE plays a key role in defining and implementing the firm's AI strategy, driving change through these capabilities, enforcing data, cloud and AI governance for the firm, and elevating Nomura's data culture.

Role Description:

• Information delivery & analytics. Deep expertise in data science with cutting-edge generative AI technologies to develop, implement, and optimize AI systems that create meaningful business value. You will work at the intersection of research and application, turning complex data into intelligent generative solutions.
• Model Development & Research. Design and develop generative AI models for various applications (text, image, code, multimodal). Research and implement novel approaches in prompt engineering, RAG systems, and model alignment. Stay current with latest research in generative AI, LLMs, and related fields
• Applied AI Solutions. Translate business requirements into generative AI technical solutions. Build and optimize retrieval-augmented generation (RAG) systems. Develop custom evaluation metrics for domain-specific generative tasks
• Be a trusted partner. Shape the information & analytics agenda at Nomura, and work with all of Nomura’s businesses in laying out their information & analytics adoption roadmaps.
• Risk Mindset: Familiar with risk and controls frameworks and ability to operate with a control mindset

Skills, experience, qualifications, and knowledge required:

Core Skills requirement:

• Proven experience developing and fine-tuning models using LLMs, diffusion models, and transformer architectures. Proficiency with frameworks such as Hugging Face, LangChain, or LlamaIndex. Working knowledge of Python libraries including pandas, NumPy, and scikit-learn for data analysis and model development.
• Demonstrated understanding of generative AI techniques, including attention mechanisms, tokenization, and embeddings. Hands-on experience applying prompt engineering, few-shot, and in-context learning for AI applications. Experience with model evaluation for generative performance, and working knowledge of responsible AI, bias mitigation, and safety frameworks. Familiarity with vector databases and semantic search systems.
• Proficiency in programming languages such as Python, SQL, and Unix shell scripting for AI and data engineering workflows.
• Experience designing, building, and deploying scalable and resilient microservices, including the development of efficient and secure server-side APIs.
• Proven experience implementing CI/CD pipelines (e.g., Jenkins, GitLab) and applying DevOps methodologies to automate deployment and integration processes.
• Experience with cloud technologies such as AWS EC2, EMR or similar tools with ability to drive design and data model discussions, hybrid data architecture.
• Experience collaborating with cross-functional and geographically dispersed teams across multiple regions to deliver AI/technology solutions.
• Proven ability to manage concurrent AI projects and meet delivery timelines in dynamic and fast-changing environments.
• Experience managing stakeholder expectations of senior management.
• Proficiency in written and verbal communication skills, with the ability to document AI processes and present technical content clearly to both technical and non-technical audiences.
• Demonstrated analytical and problem-solving skills with experience deriving data-driven insights and actionable recommendations.
• Experience evaluating business or technical requirements, identifying improvement opportunities, and proposing solutions that enhance system or business value.

Education and experience:

• At least 4-year Bachelor’s degree in quantitative fields with minimum of 5 years of relevant data experience in data scientist /Gen AI, preferably in financial organizations or Masters in quantitative fields (Computer Science, Statistics or similar)
• Experience of working with a multi-cultural, multi-disciplined, globally dispersed teams
• Professional certifications in AI/ML frameworks, cloud technologies, or DevOps tools (e.g., AWS Certified Machine Learning, TensorFlow, or Kubernetes) are advantageous.

Nomura Competencies

Explore Insights & Vision

• Identify the underlying causes of problems faced by you or your team and define a clear vision and direction for the future.

Making Strategic Decisions

• Evaluate all the options for resolving the problems and effectively prioritize actions or recommendations.

Inspire Entrepreneurship in People

• Inspire team members through effective communication of ideas and motivate them to actively enhance productivity.

Elevate Organizational Capability

• Engage proactively in professional development and enhance team productivity through the promotion of knowledge sharing.

Inclusion

• Respect DEI, foster a culture of psychological safety in the workplace and cultivate a "Risk Culture" (Challenge, Escalate and Respect).

Diversity Statement

Nomura is committed to an employment policy of equal opportunities and is fundamentally opposed to any less favourable treatment accorded to existing or potential members of staff on the grounds of race, creed, colour, nationality, disability, marital status, pregnancy, gender, or sexual orientation.

DISCLAIMER: This Job Description is for reference only, and whilst this is intended to be an accurate reflection of the current job, it is not necessarily an exhaustive list of all responsibilities, duties, skills, efforts, requirements or working conditions associated with the job. The management reserves the right to revise the job and may, at his or her discretion, assign or reassign duties and responsibilities to this job at any time.

Nomura is an Equal Opportunity Employer
SFID: 12416