Total 874 data entry job vacancies in Information Technology category in Hong Kong

Role overview 

The Digital Consultant – Data & Analytics plays a key delivery role within Turner & Townsend Japan’s Digital Consulting practice, supporting the design, implementation, and adoption of data-led digital solutions across major construction and capital projects. 

Working under the guidance of senior digital leaders, you will help translate client and internal business challenges into practical data, analytics, and insight solutions that improve project performance, predictability, and decision-making. 

This role focuses on hands-on delivery, analysis, and client engagement, contributing to digital advisory, reporting and analytics solutions, project controls data environments, and emerging AI-driven insights across Real Estate, Infrastructure, and Energy & Natural Resources sectors. 

Key responsibilities 

1. Data & Analytics Delivery 

• Support the delivery of data and analytics solutions across project, programme, and portfolio environments. 

• Develop dashboards, reports, and analytical models to support project controls, performance management, and executive decision-making. 

• Assist in data preparation, validation, modelling, and visualisation to ensure accuracy, consistency, and usability. 

• Contribute to solution testing, user training, and adoption support. 

2. Digital Advisory & Problem Solving 

• Work with project teams and clients to understand data, reporting, and insight requirements. 

• Apply structured analytical thinking to identify trends, risks, and opportunities within project and portfolio data. 

• Support the development of digital advisory outputs, including insights packs, dashboards, and recommendations. 

• Apply best practice approaches to data governance, quality, and information management. 

3. Stakeholder Engagement & Collaboration 

• Collaborate with project managers, cost managers, planners, and digital specialists to deliver integrated solutions. 

• Communicate clearly with internal teams and client stakeholders, adapting your style to different audiences. 

• Contribute to workshops, requirement-gathering sessions, and solution walkthroughs. 

• Build trusted working relationships through consistent delivery and professional conduct. 

4. Technology & Tools Enablement 

• Contribute to data environments and reporting platforms across cloud and enterprise systems. 

• Support automation of reporting and data workflows where appropriate. 

• Use standard and emerging digital tools to improve efficiency and insight generation. 

• Apply documented standards, templates, and delivery methodologies consistently. 

5. Quality, Governance & Continuous Improvement 

• Follow defined digital delivery standards, governance frameworks, and ways of working. 

• Ensure analytical outputs meet agreed quality, security, and compliance requirements. 

• Identify opportunities to improve processes, reporting, or data maturity. 

• Capture lessons learned and contribute to continuous improvement of digital services. 

6. Business Support & Growth 

• Support preparation of proposals, presentations, and client-facing materials related to data and analytics. 

• Contribute technical input to bids and pursuits under senior supervision. 

• Support development of reusable assets, templates, and analytical models that strengthen Turner & Townsend’s Digital offering. 

Key behaviours 

Love a challenge – Do better every day 

• You apply analytical and problem-solving skills to deliver practical, high-quality solutions. 

• You take responsibility for your contribution, delivering work ethically and to a high professional standard. 

• You seek opportunities to add value and improve performance through data and insight. 

Stronger together – Collaborate to deliver our best work 

• You collaborate effectively across teams and disciplines, sharing ideas and building on others’ contributions. 

• You communicate clearly and positively, adapting your approach to suit your audience. 

• You demonstrate a growing understanding of client, industry, and sustainability challenges. 

Bring out the best in everyone – Always learning 

• You actively develop your technical, consulting, and behavioural skills. 

• You seek and apply feedback to improve your performance. 

• You treat colleagues with respect, empathy, and professionalism, contributing to an inclusive environment. 

Location: Singapore (Islandwide – deployment as close to your residence as possible)
Employment Type: Contract (24 / 36 months, renewable)

About the Role

We are hiring on behalf of a leading global technology company with multiple data centers across Singapore.

This role offers a hands-on opportunity to work in a mission-critical, high-availability environment, supporting large-scale IT infrastructure. Training will be provided, making it suitable for candidates looking to build a career in data center operations.

Key Responsibilities

• Perform installation, relocation, and decommissioning of IT equipment (servers, network, storage)
• Handle structured cabling, including patching and de-patching activities
• Provide hardware break-fix support (e.g. HDD, memory, SFP modules, motherboards)
• Troubleshoot IT and network-related issues and escalate when necessary
• Support routine inspections to ensure operational integrity of data center facilities
• Assist in maintenance activities and scheduled changes
• Manage inventory of spares, tools, and RMA processes
• Coordinate and supervise external vendors on-site
• Handle access control requests and support POP site operations
• Prepare task reports and support continuous improvement initiatives
• Participate in shift duties, standby support, and after-hours activities as required

Requirements

• Minimum 1 year of experience in data center operations, OR fresh graduates with relevant technical knowledge are welcome to apply
• Basic understanding of structured cabling and IT hardware
• Hands-on experience in hardware troubleshooting or break-fix support is an advantage
• Strong problem-solving skills and attention to detail
• Ability to work in a fast-paced, operational environment
• Willingness to work shifts and be on standby when required

• 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

• 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

Your role

Our major Oil & Energy Client is looking for a Senior Data Engineer who will be accountable for designing, building, optimizing, and supporting scalable, reliable, and governed data solutions that enable operational excellence, analytics, and decision-making across LNG trading and operations. This a senior individual contributor with strong hands-on expertise across data engineering, data integration, and data platform delivery, combined with the ability to partner effectively with business and IT stakeholders in our Client's LNG business.

Data Engineering & Platform Delivery

• Design, build, and implement robust data pipelines, lakehouse patterns, and integration solutions capable of handling high volume, velocity, and variety of data
• Deliver optimized and performance-driven data solutions using cloud-native and modern data engineering practices
• Develop POCs, prototypes, and production-grade solutions, including complex SQL queries and large-scale data processing. Apply performance optimization techniques using PySpark, SQL, and distributed data processing frameworks.

Data Integration & Interface Management

• Design, build, and maintain data interfaces between Shell Energy LNG applications, enterprise platforms, legacy systems, and external partners
• Manage complex cloud-to-legacy and event-driven integration scenarios using scalable pipelines and streaming technologies
• Support day-to-day operational stability of data flows, including incident analysis, troubleshooting, and resolution in line with Shell support processes.

Data Lineage, Quality & Controls

• Define, document, and maintain end-to-end data lineage across upstream source systems and downstream consumers
• Implement data quality controls, validation rules, and exception handling aligned with Shell’s governance, risk, privacy, and security frameworks
• Contribute to enterprise data initiatives such as data catalogues, master data management, and metadata management.

Collaboration & Stakeholder Engagement

• Act as a data engineering subject-matter expert, working closely with business stakeholders, product owners, architects, and delivery teams
• Support backlog refinement, solution estimation, technical design, and release planning within Agile delivery frameworks
• Promote data engineering best practices, standards, and reusability across teams.

Operational Excellence & Continuous Improvement

• Drive improvements in reliability, observability, scalability, and performance of data pipelines
• Identify opportunities for simplification, standardization, and modernization within the data and integration landscape
• Contribute to functional excellence through the definition and maintenance of standards, methods, tooling, and patterns.

You are what we are looking for if you:

• Have 8–10+ years of relevant experience in Data Engineering and Data Integration roles
• Have proven experience delivering enterprise-grade data platforms and pipelines in cloud environments
• Are an expert in Azure, Azure Data Factory (ADF), data pipelines, Azure Data Lake Storage (ADLS), Databricks, PySpark, Python, and Kafka, with working knowledge of databases including Cosmos DB and MongoDB
• Are proficient in data modelling
• Have experience implementing performance optimization techniques using PySpark and SQL
• Have experience working with source control technologies (e.g., GitHub, Azure DevOps) and with build and release pipelines
• Have hands-on experience delivering digital solutions such as enterprise data platforms, and rolling out and setting up Master Data Management, Data Catalogue, and analytics solutions to support business decision-making
• Have experience working in Agile teams, applying best patterns and practices with an eye for quality and standards
• Have experience with Microsoft Power Platform, specifically Power Automate
• Are a Databricks Certified Associate / Professional Data Engineer (preferred)
• Have experience with LNG business stakeholders and data products (preferred)

NCCS Data and Computational Science (DCS) is a newly established computational hub within National Cancer Center of Singapore (NCCS) which focuses on leveraging data analytics and computational methods to advance cancer research and treatment. DCS features high-powered computing resources capable of processing ‘big data’ profiles and running advanced interpretable machine learning algorithms and robust statistical techniques. DCS offers in-house and centralised solutions for NCCS researchers who require computational analysis without the need to buy specialised equipment or contract with third party vendors. DCS aims to maximise the efficiency of data processes and accelerate research outcomes. With access to national level medical data spanning clinical, imaging and omics datasets, our efforts are concentrated on harvesting the innate value of these rich datasets to improve cancer patient care and treatment delivery through the production of world-class research.

The Data Scientist will provide support and insights for DCS core multi-omics research and big data analysis computing infrastructure that focus on using next-generation sequencing (NGS), radiological imaging and other multi-modal datatypes to develop biomarkers predictive of clinical responses in cancer patients. The Data Scientist will be expected to wrangle and manage large datasets, execute computational pipelines and interpret data to better understand the complexity of cancer progression and treatment resistance across multiple cancer types, as well as design new pipelines and/or optimise existing ones to meet evolving research needs.

Key Responsibilities:

- Drive and manage multiple projects: plan and perform sequencing data analyses, statistical analyses, and other relevant computational analyses and interpret the results in the context of assigned research projects/questions.

- Collaboration: Work closely with the Principal Investigator, clinicians, data scientists, researchers and stakeholders.

- Data pipeline management: Design, implement and maintain data processing pipelines for ingesting, transforming, and loading data from various sources.

- Security and Compliance: Define computing resources and data access controls, encryption, and authentication mechanisms. Ensure compliance with data privacy regulations (e.g., GDPR, PDPA, APAC Data Laws etc.) and organisation structures.

- IT Infrastructure Maintenance: Monitor system performance, identify and resolve bottlenecks or issues, ensuring minimal downtime. Apply software updates and patches. Backup data to prevent data loss. Source and liaise with vendors in procurement of the IT infrastructure to support the team's expansion needs as necessary.

Job Requirements:

- Master/PhD in Computational Biology or Computer Science or Mathematics or Biostatistics or Physics preferred.

- At least 3 years research experience in a Genomics-related field is mandatory.

- Knowledge and experience in omics analyses is mandatory (any of WGS, WES, RNAseq, single-cell sequencing or similar).

- Knowledge and experience in biostatistical analyses of clinical datasets preferred.

- Familiarity with data security and access control measures preferred.

- Ability to plan and execute data analysis and ad-hoc projects, both independently and in collaboration with external parties.

- Strong organisational, interpersonal and presentation skills.

- Familiarity with Linux or other Unix flavours, preferably as an administrator/superuser and server maintenance preferred.

- Familiarity with pipeline management systems (e.g. Nextflow), job schedulers (e.g. Slurm), container/virtualization systems (Docker, Singularity).

Role Summary

The Data Engineer will support the design, development, and operation of modern data systems and infrastructure for Data Programme. The role involves building scalable and secure data platforms, developing production-grade data pipelines, and enabling analytics, AI, and machine learning use cases across the ecosystem.

The candidate is expected to work closely with Product Managers, Data Scientists, engineers, and business stakeholders to deliver reusable, maintainable, and secure data solutions that support digital transformation objectives.

Key Responsibilities

1. Data Systems and Architecture

• Design, develop, and maintain end-to-end data systems and supporting architecture
• Build and integrate database systems, backend services, and infrastructure components to support business and analytical use cases
• Ensure solutions are designed with strong consideration for scalability, maintainability, reusability, and security
• Contribute to architecture and engineering decisions for data platforms and services

2. Data Engineering and Pipeline Development

• Develop and maintain production-grade ETL / ELT pipelines for ingestion, transformation, and delivery of data
• Build and administer databases and supporting data services for operational and analytical workloads
• Support reliable and efficient data workflows for reporting, analytics, data science, and machine learning applications
• Monitor, troubleshoot, and optimise data processing jobs, database operations, and pipeline performance

3. Cloud, DevOps and Infrastructure

• Develop infrastructure and services using modern cloud engineering practices
• Support backend, infrastructure, deployment, and operational components required for data systems
• Contribute to automation, CI/CD, monitoring, and operational readiness of data platforms
• Ensure secure and resilient deployment practices across environments

4. Cross-functional Delivery

• Work closely with Product Managers, Data Scientists, users, and other engineers to ensure solutions meet user and organisational needs
• Partner with policy and business divisions to support digital transformation initiatives through data and AI methods
• Translate requirements into implementable technical designs and engineering work items
• Participate actively in iterative product and platform delivery

5. Documentation and Support

• Document system designs, architecture decisions, data flows, and operational procedures
• Support knowledge transfer, maintainability, and operational support for delivered solutions
• Collaborate effectively across multidisciplinary teams and contribute to healthy engineering practices
• Support issue investigation, troubleshooting, and enhancement of production systems

Mandatory Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience
• Experience in data systems and architecture development, including databases, backend services, DevOps, and infrastructure engineering
• Experience developing and administering production-grade databases and data pipelines
• Strong understanding of scalable, secure, and maintainable engineering practices
• Strong communication and collaboration skills
• Interest in working on public good and supporting digital transformation in the education domain

• Experience with modern cloud-based data engineering environments
• Experience with backend development and system integration
• Experience with frontend development
• Exposure to data science and machine learning applications
• Familiarity with DevOps, CI/CD, infrastructure automation, and monitoring practices
• Experience working in agile, cross-functional product teams
• Experience in public sector, education, or mission-driven digital delivery environments

Seniority Expectations

Associate Consultant (1-3 Years)

• Supports design, development, and maintenance of data systems under guidance
• Contributes to data pipelines, database tasks, and operational support activities
• Demonstrates sound technical fundamentals and willingness to learn

Consultant (4-6 Years)

• Works independently on assigned engineering tasks and modules
• Designs and develops data pipelines, databases, and infrastructure components of moderate complexity
• Participates actively in technical discussions and cross-functional delivery

Senior Consultant (7 Years and above)

• Takes ownership of end-to-end system and architecture components
• Leads design and implementation of scalable, secure, and reusable data platforms
• Supports technical decision-making and mentors junior team members where needed
• Engages confidently with cross-functional stakeholders across product, business, and technical teams

About GoTyme

GoTyme is a joint venture between the Gokongwei Group, one of the biggest conglomerates in the Philippines, and the Singapore-headquartered digital banking group Tyme. This venture combines the trusted Gokongwei brand, customer base, and distribution ecosystem with Tyme’s globally proven digital banking technology and hands-on experience building South Africa’s leading digital bank, TymeBank, one of the fastest-growing digital banks in the world today.

At GoTyme, we have embarked on a journey to democratize financial services and bring next-level banking to the Philippines. We seek individuals who share our belief that the game is worth changing, to join our growing team of GoTymers as we build, launch, and scale a bank that empowers all Filipinos to navigate a path to financial freedom.

About the role

We are looking for a highly analytical and detail-oriented Analyst / Senior Analyst – Fraud Strategy & Analytics to join our Fraud Analytics Team. You will play a key role in developing, implementing, and optimizing fraud prevention and detection strategies across GoTyme Bank’s products and digital channels. You will analyze complex datasets, identify emerging fraud trends, and work closely with cross-functional teams to balance fraud loss mitigation with customer experience.

• Fraud Strategy & Analytics
• Monitor transactional and behavioral data to identify patterns indicative of fraudulent activity.
• Develop and enhance rule-based and model-driven fraud detection strategies for digital banking products (e.g., cards, transfers, deposits, lending).
• Conduct deep-dive investigations into fraud cases and recommend preventive actions.
• Partner with product, technology, and data teams to enhance fraud monitoring systems and controls.
• Support the design, testing, and rollout of new fraud mitigation tools and analytics capabilities.
• Prepare regular performance reports and present fraud insights to senior management.
• Participate in incident reviews, risk assessments, and process improvement initiatives.
• Innovation and Research
• Experiment with new tools, techniques, algorithms and methodologies to enhance the bank’s capabilities. 

Must Haves

• Bachelor’s degree or higher in applied mathematics, statistics, computer science, physics, data science, economics, engineering or equivalent quantitative discipline.
• 2–5 years of experience in fraud analytics or credit strategy or analytics within banking, fintech, or payments.
• Experience in first-party, third-party, or synthetic fraud risk management is preferred.
• Knowledge of machine learning techniques for fraud detection is preferred.
•  Strong SQL for data manipulation and reporting.
• Proficiency in Python for analytics, modeling, and automation.
• Exposure to AI/ML frameworks (advantageous but not required).
•  Proficiency in Excel, and/or data visualization tools (e.g., Tableau, PowerBI).
• Strong analytical problem-solving skills and attention to detail. 
• Excellent communication skills – able to present complex findings in a clear, concise manner.
• Experience in fintech, digital banking, or technology-driven financial institutions preferred.

Position: Data Analyst
Location: Singapore
Type of Employment: Full-Time
Compensation: -

Purpose of the Position: The Data Analyst will be responsible for transforming data into actionable insights to support business decision-making. This role focuses on data extraction, analysis, visualization, and reporting using modern data platforms such as Databricks, along with SQL and BI tools, to drive data-driven strategies across the organisation.

Key Result Areas and Activities:

• Extract, clean, and transform data from multiple sources using SQL and Databricks to support analytics and reporting needs.
• Develop and maintain scalable data models and datasets for business intelligence and dashboarding.
• Build interactive dashboards and reports using Tableau and/or Power BI to visualize key metrics, trends, and insights.
• Perform exploratory data analysis to identify patterns, anomalies, and opportunities for business improvement.
• Collaborate with business stakeholders to gather requirements and translate them into analytical solutions and reporting outputs.
• Support data validation, reconciliation, and quality checks to ensure accuracy and consistency of reporting data.
• Automate recurring reporting processes and improve efficiency of data workflows.
• Provide actionable insights and recommendations to support operational and strategic decision-making.
• Document data definitions, business rules, and reporting logic for governance and knowledge sharing.

Essential Skills:

• Strong proficiency in SQL for data querying, transformation, and analysis
• Experience working with Databricks or similar data platforms
• Hands-on experience with Tableau and/or Power BI for dashboard development
• Strong analytical and problem-solving skills
• Experience in data cleaning, validation, and data modelling
• Ability to work with large datasets and derive meaningful insights

Desirable Skills :

• Experience with Python (Pandas, PySpark) for data analysis
• Familiarity with cloud platforms such as AWS, Azure, or GCP
• Knowledge of ETL/ELT processes and data pipeline concepts
• Experience working in government or regulated environments
• Understanding of data governance and data quality frameworks

Qualities:

• Strong attention to detail and data accuracy
• Good communication skills to translate data insights into business terms
• Proactive and solution-oriented mindset
• Ability to manage multiple stakeholders and priorities
• Collaborative team player with strong ownership of deliverables

Overview

Build the data pipelines, models, and dashboards that turn raw market and operational data into actionable insight.

Key Responsibilities

•    Design and implement secure, performant data pipelines to aggregate, cleanse, and transform data from internal and third-party sources.

•    Build and maintain analytics data models and data Mart supporting reporting, dashboards, and downstream consumers.

•    Develop interactive dashboards and visualisations that surface trends, investment patterns, and company-level insight.

•    Implement data quality controls, validation routines, and lineage tracking to meet regulatory-grade reliability standards.

•    Integrate with market data provider APIs for ingestion, reconciliation, and profile enrichment.

•    Optimise query performance and storage across relational, columnar, and analytical workloads.

•    Partner with business analysts and stakeholders to translate analytical questions into reusable datasets.

•    Document data contracts, ETL flows, and operational runbooks.

Key Requirements (Must-Have)

•    5+ years of hands-on data engineering /analytics development experience.

•    Strong SQL across at least one of PostgreSQL, SQL Server, Oracle, or Snowflake.

•    Proficiency in Python (pandas, PySpark, SQLAlchemy) for data transformation and automation.

•    Experience building ETL / ELT pipelines using Airflow, dbt, Informatica, or equivalent.

•    Proven delivery on Tableau, Power BI, or Qlik— including parameterised dashboards and row-level security.

•    Dimensional / star schema modelling experience and comfort with slowly changing dimensions.

•    Experience with REST API integration for data ingestion.

•    Version control (Git) and CI/CD for analytics code.

•    Able to work Singapore-based, on-site at client premises a minimum of three (3) days per week.

•    Eligible to undergo and pass security clearance /background screening for financial sector engagements.

Nice-to-Have

•    Familiarity with market data platforms (e.g.,PitchBook, Tracxn, Bloomberg, Refinitiv) and financial data schemas.

•    Experience with cloud data warehouses (BigQuery, Redshift, Synapse).

•    Exposure to streaming data (Kafka, Kinesis) and CDC tooling.

•    Working knowledge of machine learning pipelines or basic predictive analytics.

•    Tableau Desktop Specialist, Azure Data Engineer, or AWS Data Analytics certifications.

•    Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative discipline.

Job Overview

We are looking for a Senior Data Engineer with strong expertise in cloud platforms and AI-driven solutions. The ideal candidate will have hands-on experience in building scalable data platforms, leading AI initiatives, and managing end-to-end delivery in a cloud-native environment.

Key Responsibilities

• Design and implement scalable data engineering solutions using cloud-native architectures on Azure and AWS
• Lead end-to-end delivery of generative AI projects or AI-powered platforms
• Translate business requirements into robust technical solutions and manage delivery timelines
• Coordinate cross-functional teams including developers, cloud engineers, and data scientists
• Provide technical leadership, mentoring, and guidance to engineering teams
• Ensure adherence to cloud security best practices, including IAM and data privacy for AI workloads
• Troubleshoot complex issues related to AI model deployment and cloud infrastructure

Key Requirements

• Strong proficiency in cloud-native architectures and services on Azure and AWS
• Proven track record in delivering Generative AI / AI-powered platforms
• Experience in technical solutioning and delivery management
• Hands-on experience working with cross-functional teams
• Strong mentoring and leadership skills
• Knowledge of cloud security, IAM, and data privacy practices
• Ability to troubleshoot complex AI and infrastructure issues

Role and Responsibilities

Roles: NGEMR Data Conversion Lead for assigned data types.

Responsibilities:

1) Follow NGEMR Data Conversion Methodology to lead the execution of data conversion projects;

2) Assist the development of data conversion project plans;

3) Collaborate with project stakeholders and teams to drive the data conversion process;

4) Adhere to project timeline and deliverables planned;

5) Report project progress and status in a timely manner;

6) Support NGEMR go-lives, investigate and fix issues.
Requirements / Qualifications

1) Bachelor Degree in Engineering or Science;

2) Good communication skills;

3) Broad and in-depth healthcare domain knowledge;

4) System integration and interfacing via HL7/SFTP/DICOM experience;

5) Good database and SQL knowledge;

6) Able to understand and analyze complex workflow scenarios;

7) Able to manage and drive multiple projects concurrently;

8) Detailed, self-motivated, positive thinking, team player.

Job Description

Technical Responsibilities

• Lead the installation, maintenance, and repair of mechanical and electrical systems, including wiring, fixtures, and equipment
• Perform advanced troubleshooting and resolve complex M&E issues
• Conduct routine inspections and preventive maintenance on electrical systems and machinery
• Interpret blueprints, technical drawings, and manuals for accurate execution
• Supervise testing and commissioning of electrical and mechanical systems

Leadership & Supervision

• Mentor and guide junior technicians and electricians
• Assign tasks, monitor progress, and ensure quality of work
• Coordinate with supervisors and project managers to meet project timelines

Safety & Compliance

• Ensure all work complies with local electrical codes and safety regulations
• Enforce proper use of PPE and adherence to safety procedures
• Conduct toolbox meetings and proactively address safety concerns

Documentation & Coordination

• Maintain accurate records of maintenance, repairs, and site activities
• Collaborate with project teams to ensure timely completion of tasks
• Communicate effectively with stakeholders to resolve site issues

Requirements

• Qualifications: Diploma or higher certification in Electrical or Mechanical Engineering. Licensed Electrician certification will be an advantage
• Experience: Minimum 5 years of relevant experience in M&E works, preferably in construction projects
• Skills: Proficient in using electrical testing tools and equipment. Strong leadership and problem-solving abilities. Good communication and team management skills