Total 4,098 job vacancies in Singapore

• 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

• Assist with ad-hoc duties as required
• Data entry, filing, and document control
• Manage emails, letters, and calls
• Process and issue invoices for orders
• Support the team with daily administrative tasks

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

Wecruit Pte Ltd

EA License No: 20C0270

Job Responsibilities:

• Billing of client, prepare invoice.
• Assist with files management and maintenance
• Data Entry and preparation of all documentation relating to AR, AP, Cashbook & GL
• Accrual& Payments, Invoicing & Receipts
• Reminder letters to client (where applicable)
• Receptionist duties
• Other general administrative duties

Job Requirements:

• Basic knowledge in Microsoft Office
• Attention to details and meticulous
• Pro-active in seeking new ideas to improve efficiencies
• Positive working attitude and good organisational skill
• Comfortable with using computer software and willing to learn
• Min. 2years of experience in admin/receptionist/accounting functions
• Qualification min. Secondary School/ Professional Certification/ Diploma

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)