Total 868 data entry job vacancies in Information Technology category in Hong Kong

For asuccessful POC, the candidate should ideally be a Mid-to-Senior level DataEngineer (3–5+ years) with the following "must-haves":

TechnicalCore

• Databricks Mastery: Expert-level knowledge of Delta Lake and the Medallion Architecture (Bronze/Silver/Gold layers).
• Apache Spark (PySpark/SQL): Ability to write optimized Spark code. For coming POC, Python is usually preferred over Scala/R for its flexibility and ecosystem.
• AWS Infrastructure: Deep understanding of S3 (Bucket policies/storage), IAM (Roles/Policies) for secure Databricks access, and VPC/Networking (Good to have)
• Data Ingestion: Experience with Databricks Autoloader or Unity Catalog for managed data governance.

"POC-Specific"Skills

• Prototyping Speed: The ability to set up a working end-to-end pipeline (Source → S3 → Databricks → OOTB BI Tool) in weeks, not months.
• Cost Management: Knowledge of how to configure Databricks Clusters (Autoscaling, Spot Instances) to prevent the POC from blowing your AWS budget.

JobDescriptions

Focus: Hands-on ETL/ELT and connectingvarious data sources and setup the platform with technical leadership.

• Role Summary:
• We are seeking a hands-on Data Engineer to spearhead our Databricks POC on AWS. You will be responsible for the initial environment setup, security configuration, and designing the framework for our future data platform.
• You will connect diverse AWS and external data sources into a unified Databricks environment.
• Key Responsibilities:
• Configure Databricks workspace integration with AWS (S3, IAM, VPC).
• Cleanse and transform raw data from S3, RDS, and APIs into Delta tables.
• Design and implement a scalable Medallion Architecture using Delta Lake.
• Build automated ingestion pipelines using Databricks Autoloader.
• Optimize Spark jobs for performance and reliability.
• Establish data governance standards using Unity Catalog. (Good to have)
• Evaluate POC success metrics (performance, cost, ease of use).

• Requirements: 3-5+ years in Data Engineering with PySpark/SQL; strong experience with AWS Glue or EMR is a plus.; Databricks Certified Data Engineer Professional preferred.

Role description

·      You are operating GlobalData Platform components (VM Servers, Kubernetes, Kafka) and applications(Apache stack, Collibra, Dataiku and similar)

·      Implement automation ofinfrastructure, security components, and Continuous Integration &Continuous Delivery for optimal execution of data pipelines (ELT/ETL).

·      Develop solutions tobuild resiliency in data pipelines with platform health checks, monitoring, andalerting mechanisms, quality, timeliness, recency, and accuracy of datadelivery are improved

·      Apply DevSecOps &Agile approaches to deliver the holistic and integrated solution in iterativeincrements.

·      Liaison and collaboratewith enterprise security, digital engineering, and cloud operations to gainconsensus on architecture solution frameworks.

·      Review system issues,incidents, and alerts to identify root causes and continuously implementfeatures to improve platform performance.

·      Be current on the latestindustry developments and technology trends to effectively lead and design newfeatures/capabilities.

Experience

·      You have 5+ years ofexperience in building or designing large-scale, fault-tolerant, distributedsystems

·      Migration experience ofstorage technologies (e.g. HDFS to S3 Object Storage)

·      Integration of streamingand file-based data ingestion /consumption (Kafka, Control M, AWA)

·      Experience in DevOps,data pipeline development, and automation using Jenkins and Octopus (optional:Ansible, Chef, XL Release, and XL Deploy)

·      Experience predominatelywith on-prem Big Data architecture, cloud migration experience might come handy

·      Hands-on experience inintegrating Data Science Workbench platforms (e.g. Dataiku)

·      Experience of agileproject management and methods (e.g., Scrum, SAFe)

·      Supporting allanalytical value streams from enterprise reporting (e.g. Tableau) to datascience (incl. ML Ops)

Skills

·      Hands-on workingknowledge of large data solutions (for example: data lakes, delta lakes, datameshes, data lakehouses, data platforms, data streaming solutions...)

·      In-depth knowledge andexperience in one or more large scale distributed technologies including butnot limited to: Hadoop ecosystem, Kafka, Kubernetes, Spark

·      Expert in Python andJava or another static language like Scala/R, Linux/Unix scripting, Jinjatemplates, puppet scripts, firewall config rules setup

·      VM setup and scaling(pods), K8S scaling, managing Docker with Harbor, pushing Images through CI/CD

·      Experience using dataformats such as Apache Parquet, ORC or Avro Experience in machine learningalgorithms is a plus.

·      Good knowledge of Germanis beneficial, excellent command of English is essential

·      Knowledge of financialsector and its products

·      Higher education (e.g."Fachhochschule", "Wirtschaftsinformatik")

Job description

Drive AI-Enabled Insights

• Deploy Natural Language Q&A and Copilot-based analytics

• Develop AI-driven use cases (forecasting, anomaly detection, KPI insights)

• Enable business users to access insights independently

Build a Scalable Data Platform

• Design and optimize data pipelines using Microsoft Fabric

• Develop robust data models and Power BI dashboards

• Standardize data architecture across the AP region

Strengthen Data Governance & Trust

• Implement Microsoft Purview for data lineage and governance

• Define data ownership and ensure KPI consistency

• Improve data quality and transparency across systems

Partner with the Business

• Translate business needs into data and AI solutions

• Act as a trusted advisor to management and operational teams

• Drive adoption of data-driven practices

Requirements

• 3–5 years of experience in data analytics, BI, or data platform roles

• Strong hands-on experience with Power BI and data modeling-Experience with Microsoft Fabric / Azure Data Platform preferred

• Exposure to AI tools (Copilot, Azure OpenAI, or similar) is a plus

• Experience in data governance (e.g., Microsoft Purview) is advantageous
  

  HOW TO APPLY:

  Interested applicants, please click on “Apply Now”. We regret only shortlisted candidates will be notified.

  Important Note: Trust Recruit Pte Ltd is committed to safeguarding your personal data in accordance with the Personal Data Protection Act (PDPA).

  Please read our privacy statement on our corporate website www.trustrecruit.com.sg.

  Trust Recruit Pte Ltd

  EA License No: 19C9950

  EA Personnel: Lim Jun Ping

  EA Personnel Reg No: R25128522

• Support the design and delivery of telecommunications systems for large-scale data centre projects, working closely with international telecom teams from concept through detailed design.
• Prepare and review telecom design documentation, including schematics, equipment layouts, cable routing plans, and calculations in line with project specifications and industry standards.
• Coordinate with architects and multi-disciplinary engineering teams to ensure telecom designs are fully integrated and aligned with project requirements and regulations.
• Conduct site inspections to verify telecom infrastructure installations, review shop and as-built drawings, and support testing and commissioning activities to ensure system performance andcompliance.
• Liaise with contractors, vendors, and project stakeholders to resolve technical issues, monitor project progress, and ensure adherence to quality, safety, and project timelines.

Requirements:

• Bachelor’s degree in Telecommunications, Electrical Engineering, or related field.
• Minimum 3 years’ experience in telecom design and site delivery, preferably in data centre or critical-facilities environments.
• Strong knowledge of structured cabling systems, fibre optics, and network connectivity.
• Understanding of industry standards (TIA/EIA, BICSI, ISO/IEC).

If this opportunity aligns with your skills and experience, please submit your resume to koh.dickson@bayesrecruitment.com

Dickson KOH, EA Registration R1103367

www.bayesrecruitment.com

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)

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