Total 992 data entry job vacancies in Information Technology category

You will...
• Ensures the data integrity during data processing.
• Verify the accuracy and validity of data processed.
• Resolve and check any quality issues raised by supervisors/clients.
• Maintain positive working relationships and open communication with local, regional and global colleagues.
• Continually innovate, develop and suggest enhancements to gain better work efficiency
• Ensure that the company’s regional and global standards are always adhered to all the times.

You have...
● Diploma or Degree in any other related fields.
● Proficiency in MS Word, MS Excel, and MS PowerPoint Ability to work independently with the ability to prioritize and multi-task; able to think rationally under pressure.
● Fresh graduates are encouraged to apply.

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 are looking to hire a Data Centre (Design) Specialist in Singapore to support our client, a top global investment bank. The ideal candidate will have relevant experience working on Data Centre design / layout.

Responsibilities:

• Work on the design and planning of Data Centre Halls with a focus on space optimization, power and cooling infrastructure.
• Work closely with vendors and DCO Engineers to align on deliverables and ensure accurate implementation
• Analyse and provide feedback on Data Centre hall plan / layout, ensuring alignment to operational and technical requirements
• Engage and collaborate with internal stakeholders, share findings and proposed plans clearly and effectively
• Identify potential risks and inefficiencies in the data centre design and propose solutions for improvement.
• Evaluate technologies proposed by vendors and assess suitability against current and emerging data center technologies

Required Skills:

• Education Background in computer science, information technology, and/or engineering field
• Possess relevant experience working on Data Centre design
• Knowledge of Data Centre power systems and cooling mechanisms
• Experience of Data Centre capacity management will be advantageous
• Strong communication and interpersonal skills, with the ability collaborate effectively with partner teams, vendors and stakeholders
• Proficiency in designing tools such as AutoCAD will be an advantage

Responsibilities

• Develop, validate, and deploy Machine Learning, Deep Learning, and Generative AI models for production environments
• Partner with business stakeholders to gather requirements and define project objectives
• Design and implement data pipelines for data preprocessing, model training, evaluation, and deployment
• Perform data validation and support data quality improvement initiatives
• Monitor, maintain, and improve analytical models and data systems
• Prepare reports and presentations to communicate findings and recommendations
• Provide technical documentation and support for deployed solutions
• Perform other tasks as assigned by the supervisor

Requirements

• Bachelors degree in Computer Science, Data Science, Engineering, or related discipline
• Internship or academic project experience in data analytics or machine learning is an advantage
• Technical Skills:
• Proficiency in Python and common data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, Keras)
• Fundamental understanding of Machine Learning and Deep Learning algorithms
• Working knowledge of SQL and relational databases (e.g., PostgreSQL, Oracle)
• Exposure to Computer Vision or Generative AI applications will be an advantage
• Experience with data visualization tools (e.g., Tableau or similar platforms) is a plus
• Basic understanding of model deployment and production environments
• Familiarity with manufacturing or industrial data will be advantageous

To apply, please visit www.gmprecruit.com and search for Job Reference: X967567Y

To learn more about this opportunity, please contact Yingying at yingying.lai@gmprecruit.com

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA Licence: 11C3793 | EA Personnel: Lai Yingying | Registration No: R1110239

• Plan and execute marketing initiatives for AI data center and immersion cooling solutions.
• Create professional content: presentations, solution briefs, case studies, and digital/LinkedIn materials.
• Drive local campaigns, webinars, and events to generate leads and strengthen client engagement.
• Collaborate closely with sales and technical teams to develop customer-facing materials and proposals.
• Represent the company professionally at client meetings and industry events.

Requirements:

• Degree in Engineering, IT, Marketing, Business, or equivalent
• At least 5 years of B2B marketing experience in data centers, IT infrastructure, AI/GPU platforms, or cooling solutions.
• Solid understanding of data center operations, rack layouts, cooling technologies, and GPU-based AI systems.
• Ability to translate technical concepts into clear value propositions for non-technical stakeholders.

If you are keen to apply for the position, kindly email your detailed resume in MS Word to hr@recruit-expert.com

Please note that only shortlisted candidates will be notified.

For more job opportunities, please visit our website at www.recruit-expert.com

EA Licence: 19C9701

Registration: R1326740

Scope of Work:

1. Data Pipeline Development & Management

• Design, build, and maintain robust data pipelines using AWS Glue
• Implement ETL/ELT processes for data ingestion from multiple sources
• Optimize data workflows for performance and scalability
• Monitor and troubleshoot data pipeline failures and performance issues

1. Data Infrastructure & Engineering (with IPOS IT Department)

• Manage and optimize AWS Redshift data warehouse operations
• Configure and maintain data storage solutions (AWS S3, data lakes)
• Implement data partitioning, indexing, and compression strategies
• Support Infrastructure as Code (IaC) for data infrastructure deployment

1. CI/CD & DevOps for Data (with AWS partners and IPOS IT Department)

• Develop and maintain CI/CD pipelines for data workflows using GitLab
• Implement automated testing for data pipelines and data quality
• Support version control and deployment strategies for data assets
• Configure AWS Lambda functions for data processing automation

1. Monitoring & Support (with IPOS IT Department)

• Set up monitoring and alerting for data pipeline health
• Provide technical support for data-related issues
• Collaborate with technical teams on data architecture requirements
• Optimize query performance and database operations

1. Documentation & Reporting (with IPOS IT Department)

• Document data pipeline architectures and technical specifications
• Maintain runbooks and operational procedures
• Conduct monthly progress meetings (1 hour) to report on system health
• Track engineering tasks through SHIP-HATS Jira
• Maintain technical documentation on SHIP-HATS Confluence

Required Skills & Experience:

• Strong background in data engineering and data pipeline development
• Proficiency in SQL, Python, and shell scripting
• Extensive experience with AWS data services (Redshift, S3, Glue, Lambda, CloudWatch)
• Data warehouse design and optimization experience
• Strong CI/CD pipeline knowledge (GitLab preferred)
• Infrastructure as Code (IaC) experience (Terraform, CloudFormation)
• Knowledge of data modeling and database design principles
• Strong troubleshooting and performance optimization skills

What we do matters
Azendian Solutions, an AI, Data Science and Operations Technology company, develops solutions for energy and resource optimisation to achieve a smarterand more sustainable Built Environment by reducing carbon footprint, enhancing resource productivity and operations as well as lowering costs. Our AI-driven solution is game changing in its approach, leveraging on Machine Learning, Data Science, Cloud Computing with Operations Technology engineering systems.

What you will do

• Build and maintain data pipelines to process data from building systems and IoT devices
• Work with real-world engineering data (e.g., equipment performance, energy usage)
• Support development of analytics and AI models for:
• Anomaly detection
• Predictive maintenance
• Performance optimization
• Assist in setting up systems and environments for Databases (SQL), basic server setup (Windows/Linux) and running applications using Docker or microservices
• Use modern tools (including AI-assisted tools) to improve productivity and workflows
• Collaborate with engineering and product teams to deliver real-world solutions

Core Responsibilities

·      Data Engineering & Pipeline Development

·      Data Integration (BMS / IoT Systems)

·      Analytics & AI Enablement

·      Data Quality & Performance Optimization

·      Collaboration & Delivery

Job Requirements

·           Diploma or equivalent in Electrical/Electronic Engineering or Computing Engineering, Information Technology or related field.

·           Minimum 1 year of relevant experience in data engineering, software engineering, or engineering systems.

·           Strong foundation in Python and SQL (MSSQLand/or PostgreSQL).

·           Familiarity with data processing, ETL pipelines, or data management concepts.

·           Experience or interest in working with real-world data (e.g., IoT, engineering systems, or operational data).

·           Knowledge in BMS communication protocols (BACnet and Modbus) is preferred but not required.

·           Basic familiarity with system setup (e.g databases, Windows/Linux environment, or Docker) is an advantage.

·           Experience with workflow orchestration tools (e.g., Airflow, Prefect) is a plus.

·           Exposure to data analytics or machine learning concepts is a plus.

·           Familiarity with AI-assisted tools or automation tools is an advantage.

·           Strong logical and analytical skills.

·           Willingness to learn and work across data systems, and AI domains.

·           Able to work comfortably and independently in a fast-paced environment.

You own the storage layer and cloud infrastructure provisioning. You design the multi-tenant data architecture that makes IP isolation possible and auditable: shared public data stores for market data, and per-tenant isolated stores for proprietary data. Every table, bucket, and index is either explicitly shared or explicitly tenant-scoped. You provision all infrastructure as code and ensure that onboarding a new tenant is a scripted operation, not a manual one.

Responsibilities

• Provision all cloud infrastructure via Terraform: object storage, vector databases, event streaming, Kubernetes, time-series databases, authentication. All reproducible for new tenants.
• Design multi-tenant storage: shared vector indices for public data, per-tenant indices for proprietary data. Row-level security or schema-level isolation.
• Design per-tenant storage structure with bucket policies enforcing isolation.
• Build market data storage pipeline: exchange feeds → event bus → time-series database.
• Build monitoring dashboards for data pipeline health across all data sources.
• Design feedback data storage: per-tenant schema for feedback events and training data candidates.
• Build data archival pipelines for cost-efficient long-term storage.
• Automate tenant provisioning: a script that creates a new tenant’s storage, network policies, and service accounts.

Requirements

• 4+ years data engineering; strong SQL, Python, and cloud infrastructure.
• Experience designing multi-tenant data architectures with isolation requirements.
• Infrastructure as Code: Terraform or Pulumi — mandatory.
• PostgreSQL experience (vector extensions, partitioning, row-level security a plus).
• Kafka consumer/producer development.
• Time-series data storage and querying experience.

Nice to have

• Experience with financial data: time-series, tick data, on-chain events.
• Understanding of data sovereignty and compliance requirements.
• Experience with tenant provisioning automation.
• Blockchain or crypto data pipeline experience.

Company Overview

Infogain Solutions is a leading IT services company specializing in IT solutions, staffing, and recruitment across industries including financial services, IT, and audit firms. We connect professionals with organizations to drive business growth and innovation.

Job Summary

As a Data Engineer, you will design and implement scalable data pipelines and infrastructure using Spark, Hadoop, and container platforms to support large-scale data processing and analytics.

Responsibilities

• Design, develop, and implement Spark Scala applications and data pipelines to process large volumes of structured and unstructured data efficiently
• Integrate Elasticsearch with Spark to enable effective data indexing, querying, and retrieval
• Optimize Spark jobs for performance and scalability to ensure efficient data processing and indexing in Elasticsearch
• Collaborate with data engineers, data scientists, and stakeholders to translate requirements into technical specifications and solutions
• Design and deploy data engineering solutions on OpenShift Container Platform using containerization and orchestration techniques
• Optimize containerized data workflows for efficient resource utilization and deployment
• Work with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and maintain platform stability
• Monitor and troubleshoot data pipeline performance issues, implementing enhancements to improve reliability and efficiency
• Implement monitoring and logging mechanisms to ensure data infrastructure health, availability, and performance
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference
• Stay current with emerging technologies, industry trends, and best practices in data engineering and DevOps
• Provide technical leadership and mentorship to junior team members to foster continuous learning and innovation

Required competencies and certifications

• Bachelor's degree in Computer Science, Data Engineering, Information Technology, or related field
• Minimum 10 years of experience as a Data Engineer working with Hadoop, Spark, and large-scale data processing technologies
• Expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Ranger)
• Experience with containerization platforms such as OpenShift Container Platform and Kubernetes orchestration
• Proficiency in programming languages used in data engineering such as Spark, Python, Scala, or Java
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools including Docker, Jenkins, Ansible, and BitBucket
• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges
• Excellent collaboration and communication skills to work effectively with cross-functional teams
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment

Preferred competencies and qualifications

• Experience with monitoring tools such as Grafana, Prometheus, and Splunk
• Experience with cloud platforms and their data services (e.g., AWS, Azure, GCP)

Role Overview

We are seeking a skilled Data Analyst / BI Developer to develop and maintain Oracle database solutions, build interactive dashboards, and deliver actionable business insights. The successful candidate will collaborate with cross-functional stakeholders to support data-driven decision-making across the organisation.

Roles & Responsibilities

• Develop, maintain, and optimise Oracle database stored procedures to support business intelligence and reporting needs.

• Design, build, and manage interactive dashboards and reports using Qlik Sense (preferred) or Tableau.

• Analyse large datasets to identify trends, patterns, and actionable insights.

• Collaborate with stakeholders to gather requirements and translate them into technical solutions.

• Ensure data quality and integrity by performing data validation and cleansing activities.

• Automate repetitive reporting tasks to improve efficiency.

• Document data processes, procedures, and dashboards for knowledge sharing and future reference.

• Provide ad-hoc analysis and support to various business units as needed.

Collaborate with cross-functional teams to identify data needs and develop effective solutions.

Primary Skills

• Oracle DB stored procedures — strong skills and working knowledge.

• Dashboard reporting — Qlik Sense (preferred) or Tableau.

• Strong analytical skills and data analysis acumen.

• Strong understanding of Oracle DB query scripting.

• 1–2 years of hands-on experience in machine learning or Python for data analytics pipelines.

• Experience in dashboard visualisation tools (Qlik Sense preferred).

• Familiarity with Oracle stored procedure format.

Good-to-Have Skills (Optional)

• Familiarity with Agile processes and tools to support the SDLC.

• SAS (Statistical Analysis System) knowledge and experience.

Practical working experience in Python scripting for ETL processes.

Key Responsibilities

• Enterprise Data Strategy
  Define and lead the enterprise data strategy and roadmap aligned with business, regulatory, and operational priorities. Drive initiatives to strengthen data governance, management, and analytics capabilities, while promoting data literacy and responsible data usage across the organisation.
• Enterprise Data Governance
  Establish and implement the data governance framework, including policies, standards, and operating model. Define data ownership and stewardship, and set up governance forums to ensure accountability and consistency across business units.
• System of Record & Data Standards
  Define and maintain System of Record (SoR) and Single Source of Truth (SSOT) principles. Standardise data definitions, master data structures, and enterprise data domains to ensure consistency in reporting and decision-making.
• Data Quality & Trusted Data Foundations
  Implement data quality frameworks, controls, and monitoring processes. Establish validation, reconciliation, and exception management standards, while reducing reliance on manual processes and enabling trusted datasets for reporting and analytics.
• Regulatory Data Governance & Risk
  Ensure data governance practices meet regulatory, compliance, and audit requirements. Implement data lineage, documentation, and certification standards, and collaborate with Risk and Audit teams to strengthen governance controls.
• Data Architecture Governance
  Define and oversee enterprise data architecture principles and standards. Work closely with IT to ensure systems, integrations, and data pipelines align with governance requirements and support scalable data management.
• Data & Technology Partnership
  Partner with IT and business leaders to embed data governance into systems and platforms. Support the development of enterprise data and analytics capabilities, ensuring reliable and consistent reporting across the organisation.

Requirements

• More than 10 years’ experience in datamanagement, governance, or data architecture leadership
• Degree in Information Systems, Computer Science,or related field
• Proven track record in establishing enterprisedata governance frameworks and operating models
• Experience with enterprise data platforms andanalytics tools (e.g. Snowflake, Qlik)
• Strong exposure to complex environments withmultiple systems and data domains
• Strong stakeholder management with ability toinfluence senior leadership
• Solid knowledge of data governance, dataquality, and master data management
• Ability to translate business needs into datastrategy and governance frameworks
• Proven experience leading cross-functionaltransformation initiatives
• Relevant certifications (e.g. CDMP, DCAM, TOGAF)are advantageous
  

License No. 22C1076 | EA Reg: R2615945

• Award-Winning Superannuation Fund Provider 
• Driving the data quality vision and roadmap
• Purpose-led work: help us create super our members love
• Sydney Located | Hybrid working - blend CBD Office / Home 

Established in 1988, Rest is one of Australia’s largest profit-to-member superannuation funds. We support more than two million members, with around $100 billion of funds under management and are recognised as a responsible investment leader*. We believe when members understand and engage with their super, they’re more likely to get a better retirement outcome.

Everything we do at Rest is underpinned by our values and behaviours, we want to Be Daring, Keep it Simple, Take Action and Have Grit. To put it simply we want our people to thrive and love the work they do.

About the role

The Data Quality Management Lead defines and delivers Rest’s enterprise data quality vision, objectives and roadmap. The role leads delivery to uplift data literacy and maturity, ensure Rest meets compliance and data quality risk obligations, and embed processes that support good‑practice data quality. The Data Quality Delivery team is responsible for: -

• Driving the data quality vision and roadmap
• Implementing data quality best practices at Rest
• Protecting Rest’s most important data assets (Critical Data Elements)
• Uplifting the data quality knowledge and skills of our people

What you'll do 

• Lead and maintain the data quality capability roadmap with key data stakeholders.
• Embed data quality management into the delivery and maintenance of enterprise data assets through fit‑for‑purpose tools and processes.
• Build and support data communities of practice and uplift data literacy across Rest.
• Own the evaluation and selection of data quality tools, informed by business needs and market trends.
• Design and maintain operational processes for identifying, prioritising and monitoring Critical Data Elements.
• Partner with the Data Governance Lead to embed data quality and governance into key data delivery processes (e.g. Data Design Authority).
• Oversee data quality management and ongoing governance for prioritised CDEs on Rest’s strategic data platform.
• Work effectively within agile ways of working.

This role is required to design and build high volume backend data processing systems for Razer’s Artificial Intelligence (AI) gaming products. The ideal candidate is responsible for developing and implementing data pipelines, data storage systems, and backend application software, while working closely with frontend engineers, data scientists, and machine learning engineers to enable Gen AI capabilities.

Essential Duties and Responsibilities

• Design and implement data systems that enable the organization to store, process, and analyze large volumes of data. This involves developing data pipelines, designing scalable data processing systems in support of Gen AI capabilities.
• Manage data lakes, knowledge bases, and application databases. This involves creating and managing table schemas, views, materialized views, including tokenization techniques for Gen AI.
• Develop and templatize data pipelines that enable high volume extract, transform, and load operations from various sources – particularly API-based or web-based data ingestion.
• Design, develop, and maintain highly performant, scalable, and robust backend systems and server-side logic - including maintenance and optimization of backend infrastructure for changing product requirements.
• Collaborate with data scientists and machine learning engineers to understand the data needs of various stakeholders across the organization and integrate appropriate solutions.

Requirements

• Ability to work in fast paced, high pressure, agile environment.
• Ability and willingness to learn and apply new technologies
• Strong in programming languages such as Python, SQL.
• Experience in developing and deploying applications running on cloud infrastructure such as AWS, Azure or Google Cloud Platform using Infrastructure as code tools such as Terraform, containerization tools like Dockers, container orchestration platforms like Kubernetes
• Experience in system design and building scalable, high concurrency user applications
• Familiarity with a wide variety and genres of video games, and the gaming industry in general.
• Excellent with various data processing techniques (streaming, batch, event-based), managing and optimizing data storage (Data Lake, Vector Data Stores and Database, SQL, and NoSQL) is essential.
• Excellent problem-solving and analytical skills, with an understanding of Gen AI technologies and their applications
• Experience using orchestration tools like Airflow or Prefect is preferred
• Excellent written and verbal communication skills for coordinating across teams.
• Experience and Interest to keep up with the advancement in the Data Engineering Field
• Has a Bachelor's or Master’s degree in computer science or similar discipline.

Job Responsibilities:

• Data Analysis & Trend Identification:

  • Analyze large datasets to identify key trends, patterns, and correlations across the BreadTalk Group.

  • Provide data-driven insights to help the leadership team make informed decisions and define strategic directions for the business.

• BTGR Data Management:

  • Take ownership of managing and analyzing BTGR data, focusing on member profiles, demographic analysis, divisional sales, transaction counts, SKU performance, and store performance.

  • Ensure data accuracy and consistency across all data touchpoints.

• Strategic Recommendations:

  • Work closely with the brand and management teams to deliver strategic recommendations based on data analysis.

  • Assist in determining the right strategic moves for various brands within the BreadTalk Group, based on insights gained from data.

• Data Extraction & Reporting:

  • Extract, consolidate, and analyze data from multiple sources and systems, ensuring data integrity.

  • Generate comprehensive reports for stakeholders, addressing data discrepancies and ensuring accurate, timely reporting.

• Cross-Departmental Collaboration:

  • Collaborate with various departments (Marketing, Finance, Operations, etc.) to ensure alignment of data insights with business needs.

  • Assist teams in improving business processes through data-driven decision-making.

• Customer Service Analytics:

  • Analyze customer service data to identify areas for improvement, enhancing service quality and customer satisfaction.

Job Requirements:

• Education: Diploma/Bachelor’s degree in Data Science, Statistics, Business Analytics, or a related field.

• Experience: Candidates with relevant internship experience are welcome to apply. 0-2 years of experience in data analysis, business intelligence, or a related role, preferably in retail, F&B, or a similar industry.

• Technical Skills:

  • Proficiency in data analysis tools (e.g., SQL, Excel, Python, R, or similar).

  • Experience with data visualization tools (e.g., Tableau, Power BI).

  • Strong knowledge of data management and reporting processes.

• Soft Skills:

  • Strong analytical and problem-solving skills.

  • Excellent communication and presentation skills.

  • High attention to detail and accuracy in reporting.

  • Ability to work collaboratively with cross-functional teams.

Other: Knowledge of customer analytics and sales performance metrics is a plus.

About the Job

We are seeking a skilled and detail-oriented Data Engineer to design, develop, and maintain robust data pipelines and ETL solutions. This role involves working closely with cross-functional teams to ensure data quality, scalability, and alignment with business and technical requirements.

• Design, develop, test, and maintain scalable ETL pipelines to meet business, technical, and user requirements.
• Collect, refine, and integrate new datasets. Maintain comprehensive documentation and data mappings across multiple systems.
• Create optimized and scalable data models that align with organizational data architecture standards and best practices.
• Drive continuous improvement in data quality through optimization, testing, and solution design reviews.
• Ensure all solutions conform to big data architecture guidelines and long-term roadmap.
• Implement robust monitoring, logging, and alerting systems to ensure pipeline reliability and data accuracy.
• Apply best practices in data engineering to design and build reliable data marts within the Hadoop ecosystem for planning, reporting, and analytics.
• Maintain and optimize data pipelines to ensure data accuracy, integrity, and timeliness.
• Manage code in a centralized repository with clear branching strategies and well-documented commit messages.
• Coordinate with stakeholders to ensure smooth production deployment and adherence to data governance policies.
• Proactively identify and implement improvements to data engineering processes and workflows.
• Develop end-to-end solutions for data modeling in the data warehouse, including data acquisition, contextualization, and integration with business processes.
• Ensure adherence to development standards and perform periodic reviews to maintain pipeline performance and sustainability.
• Coordinate and conduct testing with stakeholders to ensure effective deployment of data pipelines and dashboards.
• Serve as the primary data engineering contact at the stakeholder location, ensuring clear communication and alignment on priorities
• Monitor data pipelines continuously and collaborate with stakeholders to troubleshoot and optimize performance.
• Leverage domain knowledge in insurance to design data models and pipelines that support business processes and analytics.
• Work closely with business stakeholders to understand requirements and translate them into scalable data engineering solutions.

We are looking for people who

• Diploma with at least 10 years’ working experience, preferably in Life Insurance
• Proven experience in data engineering, ETL development, and big data technologies
• A strong team player who is meticulous, detail-oriented, and capable of performing under pressure
• Proficiency in tools and platforms such as Hadoop, Spark, Hive, and cloud data services (e.g., AWS, Azure, GCP).
• Possesses strong problem-solving and interpersonal skills.
• Committed, dependable, and adaptable with the flexibility to support during peak periods and tight deadlines
• Demonstrate high integrity, accountability, and a collaborative mindset
• Takes initiative to improve current state of things and embrace change

How you succeed

• Champion and embody our Core Values in everyday tasks and interactions.
• Demonstrate high level of integrity and accountability.
• Take initiative to drive improvements and embrace change.
• Take accountability of business and regulatory compliance risks, implementing measures to mitigate them effectively.
• Keep abreast with industry trends, regulatory compliance, and emerging threats and technologies to understand and highlight potential concerns/ risks to safeguard our company proactively.

Who we are

Founded in 1908, Great Eastern is a well-established market leader and trusted brand in Singapore and Malaysia. With over S$100 billion in assets and more than 16 million policyholders, including 12.5 million from government schemes, it provides insurance solutions to customers through three successful distribution channels – a tied agency force, bancassurance, and financial advisory firm Great Eastern Financial Advisers. The Group also operates in Indonesia and Brunei.

The Great Eastern Life Assurance Company Limited and Great Eastern General Insurance Limited have been assigned the financial strength and counterparty credit ratings of "AA-" by S&P Global Ratings since 2010, one of the highest among Asian life insurance companies. Great Eastern's asset management subsidiary, Lion Global Investors Limited, is one of the leading asset management companies in Southeast Asia.

Great Eastern is a subsidiary of OCBC, the longest established Singapore bank, formed in 1932. It is the second largest financial services group in Southeast Asia by assets and one of the world’s most highly-rated banks, with an Aa1 rating from Moody’s and AA- by both Fitch and S&P. Recognised for its financial strength and stability, OCBC is consistently ranked among the World’s Top 50 Safest Banks by Global Finance and has been named Best Managed Bank in Singapore by The Asian Banker.

To all recruitment agencies: Great Eastern does not accept unsolicited agency resumes. Please do not forward resumes to our email or our employees. We will not be responsible for any fees related to unsolicited resumes.

Data Centre Engineer (1-Year Contract)

Company: Leading Banking Institution
Location: Singapore
Employment Type: 1-Year Contract (Completion Bonus Provided)
Work Schedule: 24x7 Environment (On-call rotation required)

Role Overview

We are seeking an experienced Data Centre Facilities Engineer to support and maintain critical infrastructure within a high-availability banking environment. This role is pivotal in ensuring the reliability, security, and operational efficiency of the data centre.

Key Responsibilities

• Monitor and maintain critical data centre infrastructure, including power systems (UPS, generators), HVAC, fire suppression, and structured cabling
• Coordinate with building landlords and vendors to ensure timely preventive maintenance and compliance with safety standards
• Respond to system alarms, troubleshoot issues, and drive prompt resolution
• Support after-hours activities, including on-call duties and emergency response
• Ensure adherence to data centre physical security policies and procedures
• Follow incident management processes, track issues to closure, and provide timely updates to stakeholders
• Prepare management reports including performance metrics, incident summaries, and root cause analysis
• Support ongoing operational improvements and infrastructure-related projects

Key Requirements

• Minimum 5 years of experience in data centre facility management
• Proven experience in 24x7 high-availability environments (on-call support required)
• Strong knowledge of:Electrical systems (UPS, generators)HVAC systemsFire suppression systems
• Familiarity with structured cabling and rack-and-stack activities is an advantage
• Good understanding of ITIL-based incident, problem, and change management
• Strong troubleshooting and problem-solving skills
• Excellent communication and stakeholder management abilities
• Mandatory: Prior experience in data centre operations within a financial institution