Total 696 Full-time data entry job vacancies

Job Descriptions:

• Check timecard against Info-tech clocking, enter the time hours, and ensure absent days are not given hours by the supervisors.
• Update and ensure accuracy of infotech database (eg. new join, cancellation, Home Leave records, basic salary, wp expirydates, csoc expiry dates, passport expiry dates & etc).
• Enforce strict controls on advances/loans—record, prepare bank file and recover fully.
• Ensure allowance and deductions are reflected in the payroll.
• Finalize data entries of payroll hours by the 5th; submit bank files by the 6th or latest 7th.
• Resolve bounced payments quickly.
• Finalise cash salary amount and coordinate toget the cash ready by the 8th.
• Keep the HR team & HOD informed of anypayroll queries and respond to workers/ supervisors within 2 working days.
• Submit job costing reports by the 10th.
• Issue payslips by the 14th.
• Check and tally balance of loan to workers against records of Finance Department on a monthly basis.
• Prepare and ensure original vouchers, loan agreements, payslips of cash salary, and etc are signed, returned, and scanned to server.
• Keep track of salary advances and giro transfers in Excel in a timely manner.
• Update and ensure accuracy of the increment excel in a timely manner.
• Prepare for settlement of salary, IR21 tax clearance, salary payment (including bank files for approver) for Home Leave Workers/ Resigned Workers and update in Excel in a timely manner.
• Check and submit yearly Employment Income IR8A.
• Prepare the required documents and respond to queries raised by the Finance auditor.
• Apply for levy waiver.
• Support ad-hoc tasks (e.g., Provide name list and payroll information for top management/ surveys/ policy renewals/submissions).
• Apply for bank accounts and distribute ATM cards in return with workers’ acknowledgements.
• Monitor passport and CSOC expiry dates, arrange timely renewals, and register workers for CSOC classes as needed.
• Maintain petty cash records.
• Reply to WhatsApp messages promptly.

Requirements:

• Available to start immediately.
• Fresh graduates are welcome. We can teach.
• Knowledge with Infotech Payroll & TMS modules is an advantage.
• Detail-oriented, proactive, and patient.
• Consistently having the passion to improve your work procedures and bring up to the team fordiscussion.
• Problem-solving and flexible thinking.
• Clear communication across all levels.
• Responsible team player—plan leave to avoid payroll timelines.

Roles & Responsibilities

Position: Data Entry Coordinator (Operations)

Location: Singapore 

About the Role: We are seeking a detail-oriented and dedicated Data Entry Coordinator to join our team. The successful candidate will be responsible for accurately inputting, updating, and maintaining operational records, ensuring data integrity and confidentiality at all times.

Key Responsibilities:

• Enter and update information into databases and spreadsheets.

• Verify accuracy of data and correct errors when identified.

• Maintain organized filing systems (digital and physical).

• Ensure compliance with company policies and data protection standards.

• Provide administrative support to other departments when required.

Requirements:

• Strong attention to detail and accuracy.

• Proficiency in Microsoft Office (Outlook, Excel, Word) and data management systems

Applicants who possess relevant experience for the above responsibilities are most welcome to apply. If you do not possess the above experience, your application will still be considered on individual merits and you may be contacted for other opportunities.

By submitting your personal data and/or resume, you give consent to the collection, use and disclosure of your personal data and/or resume by the company for the purpose of processing and administration by the company relating to this job application.

We regret to inform only shortlisted candidates will be notified.

Job Description:

• Data entry for Finance Department
• 3 days per week
• Working Hours - 0800 - 1730

Requirements:

• Computer Literate
• Training will be provided

Work scope, duties and responsibilities

1. Perform Quality administrative duties including data entry, document management.

2. Coordinate & assist in sorting, filing, and copying documents.

3. Any other duties and responsibilities assigned by the Company from time to time

Working Day/ Time : Tuesday to Saturday, 8.30am to 6pm (5 days)

Our client is a prominent data center and ICT services provider based in Singapore. It specializes in offering secure, scalable, and high-performance infrastructure solutions to enterprises, financial institutions, and government agencies.

Job Scope:

• Support Engineers and Senior Engineers in performing maintenance and operational tasks as required.
• Respond to system alarms or faults, analyze patterns, and assist in implementing appropriate corrective measures.
• Monitor and investigate alerts from the Building Management System (BMS) and Environmental Monitoring System (EMS)
• Provide updates on unresolved issues, respond to emergencies, and be available for standby duties.
• Contribute to data center projects and additional or alteration works, including construction activities, equipment installations, and coordination with external contractors to ensure compliance with operational standards and project timelines.
• Assist in both scheduled and emergency maintenance events, and support efforts related to accreditation and certification processes.

Requirements:

• Degree in Electrical/Mechanical Engineering or equivalent
• No experience needed (Training provided)
• Able to commit to 12 hours rotating shift duty

Working Location: Bedok/Woodlands

Salary: Up to $3,800 + AWS + Variable bonus

To apply, kindly click APPLY NOW to submit your latest CV.

We regret that only shortlisted candidates will be notified.

Job Description:
We are looking for a dedicated and disciplined Production Data Entry Assistant (System & Tracker) to support our Production Manager in daily operations. This role is responsible for accurate and timely entry of work orders into production trackers (manual and digital), ensuring real-time visibility of job progress and full traceability across all stages.

In the future, the role will also involve working with the Manufacturing Execution System (MES)once implemented. The data you provide will be critical in helping the Production Manager plan, assign, and monitor tasks across the production team.

Key Responsibilities:

• Perform accurate and timely data entry of daily work orders into production trackers (manual & digital).
• Provide live updates on job status for traceability across different production stages.
• Support the Production Manager with reliable data for daily planning and task allocation.
• Maintain proper records and documentation of all production work orders.
• Liaise with production staff to capture and update live job status.
• Adapt to future system implementation (e.g., MES) to enhance data accuracy and efficiency.

Requirements:

• Strong discipline, accuracy, and commitment to role responsibilities.
• Fast learner with the ability to quickly understand production processes and workflows.
• Organized, firm, and detail-oriented, able to work under pressure in a fast-paced production environment.
• Basic computer literacy (Microsoft Excel, Word, data entry).
• Prior experience in manufacturing/production administration will be an advantage.

Overtime eligible, based on production requirements

The Reference Data Specialist is responsible for instructions of client deliverables, coding and data input validation focusing on specific industry/category or set of categories (e.g. Beverages, Food, Health and Beauty Products). As a Reference Data Specialist  at NielsenIQ, you create and deliver client outputs in a correct and timely manner.

• Responsible for instructions of client deliverables, coding and data input validation focusing on specific industry/category or set of categories.
• Does cross coding and item-related quality checks on a daily basis
• May act as a back-up to other coders when needed; Keep track/document special instructions related to category assignment
• Plan and execute a complex daily personal workload and support to meet departmental and company schedules
• Ensure accuracy throughout the process, from validation before database setup to managing samples, and identify areas for improvement
• Answer external questions and act as a liaison with everyone from clients to stakeholders; To be able to identify, investigate and coordinate the resolution of data, process, or product related queries
• Willing to be trained to be a category expert

Purpose of Role:

Assist in the development of ILS deliverables for ILS programmes that meets customer requirements efficiently and on time.

Responsibilities:

• Responsible for data entry and document assembly or extraction.
• Creating and populating data into templates for codification
• Processing and doing MMD data entry into software system • May be required occasionally to be at external site to assist for coordination of delivery of items to store
• May be required occasionally to be at external site for coordination of training
• Occasional lifting and carrying of documents or parts is required.

Requirements:

• Good proficiency in MS Office Suite
• Experience in Document Control for engineering projects will be advantageous
• Good written, verbal communication skills in English is required
• Able to interact effectively with all levels of staff both internally and externally
• Able to work independently
• Willing to commit to 2 years contract

Additional Information:

• Location: 16 Benoi Road (Island-wide transport provided)
• 5 days work week
• Working Hours: 7.25am to 5.00pm

About the job

Reporting to the Data and Analytics Lead, the successful candidate will be responsible for the following:

Data Management & Transformation

• Designing and developing new data pipelines and managing existing data pipelines that extract data from various business applications, databases, and external systems.
• Implementing data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data.
• Transforming data into the desired format by applying data cleansing, aggregation, filtering, and enrichment techniques.
• Establishing the governance of data and algorithms used for analysis, analytical applications, and automated decision-making.
• Manage the logical and physical data models to capture the structure, relationships, and constraints of relevant datasets.
• Ensuring compliance with security and governance best practices.

Optimization & Automation

• Implementing and maintaining continuous integrations and continuous delivery pipelines for deployments and cloud resource provisioning.
• Optimising data pipelines and data processing workflows for performance, scalability, and efficiency.
• Optimising models and algorithms for data quality, security, governance, performance and scalability needs.
• Routinely assessing processor and storage capacity across the data warehouse and extract, transform & load platforms, including capacity planning and forecasting.
• Monitoring and tuning the data system, identifying and resolving performance bottlenecks and issues, and implementing caching and indexing strategies to enhance query performance.
• Monitoring the platform for credit consumption and housekeeping.
• Supporting the deployment and maintenance of AI solutions in the data platform.

Collaboration

• Working with the data lead and business users to manage data as a business asset.
• Guiding the business users to create and maintain reports and dashboards.

Requirements:

• Bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field; Master’s degree preferred.
• At least ten years of work experience in data management disciplines, including data integration, modelling, optimisation, and data quality, or other areas directly relevant to data engineering responsibilities and tasks.
• At least four years of work experience in designing and implementing data architectures in Azure cloud services and Databricks.
• Strong proficiency in Python (PySpark) and SQL programming; experience with Java or Scala is an advantage.
• Experience with relational and non-relational databases, including SQL and NoSQL, is a must, while familiarity with legacy databases such as Oracle is preferred.
• Experience using Azure DevOps, Databricks LakeFlow Jobs for DevOps practices, including version control, CI/CD and pipeline deployment.
• Experience with data catalogue tools, including Unity Catalogue and Microsoft Purview.
• Familiarity with BI & visualisation tools such as Power BI and Python visual packages for data analytics is preferred.
• Experience supporting AI/ML model deployment, feature engineering and production inference is preferred.
• Align with and demonstrate the company's Core Values, which are Integrity, Teamwork, Accountability, Agility, and Ambition.

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Key Responsibilities

Integration & Workflow Engineering

• Analyse and re-platform existing workflow-based integrations from one platform to another while maintaining functional parity.
• Implement orchestration logic including triggers, conditional routing, retries, exception handling, and state management.
• Design and implement automation patterns to handle platform limitations (e.g., looping, batching, pagination, throttling).
• Ensure workflows are idempotent, fault tolerant.
• Support environment-based deployments (DEV / UAT / PROD) with configuration-driven designs.

Data Engineering & ETL

• Design and build ETL pipelines for ingesting flat files (e.g., CSV) into relational databases.
• Handle schema validation, basic schema evolution, data quality checks, and error reconciliation.
• Optimize data ingestion for performance, scalability, and reliability.
• Collaborate with application teams to understand upstream and downstream data dependencies.

Cloud & Big Data Platform Contributions

• Build and maintain data pipelines on cloud-based big data platforms using distributed processing frameworks.
• Contribute to Lakehouse-style data storage that supports both batch and streaming data.
• Work with modern table formats that support incremental processing, versioning, and historical queries.
• Support use cases such as append-heavy datasets, high-write event data, and analytical queries.

Operations, Quality & Observability

• Implement logging, monitoring, and alerting for workflows and data pipelines.
• Support operational readiness including runbooks, deployment procedures, and rollback strategies.
• Participate in root-cause analysis and continuous improvement of data pipelines.
• Ensure adherence to data governance, security, and compliance standards.

Required Skills & Experience

Technical Skills

• Strong experience with workflow orchestration / integration platforms.
• Solid understanding of ETL concepts and hands-on experience with file-based ingestion.
• Proficient in SQL and working knowledge of relational databases (e.g., SQL Server or equivalent).
• Experience with distributed data processing frameworks (e.g., Spark).
• Familiarity with streaming and batch data processing concepts.
• Practical experience with cloud platforms and managed data services.
• Understanding of CI/CD principles for data and integration workflows.

Programming & Automation

• Experience with scripting or programming languages commonly used in data engineering (e.g., Python).
• Ability to build reusable utilities for batching, retries, pagination, and error handling.
• Experience with REST APIs and structured data formats (JSON, CSV).

Desired (Good to Have)

• Exposure to modern Lakehouse table formats supporting incremental processing and time travel.
• Experience with stream processing engines (e.g., Flink or Spark Streaming).
• Familiarity with query engines used for analytical access.
• Experience working in regulated environments (banking, financial services, or manufacturing).
• Knowledge of data observability and quality frameworks.

Experience Level

• Typically, 3–5 years of relevant experience in data engineering, integration engineering, or similar roles.
• Proven ability to work independently on moderately complex problems while collaborating within a larger team.

Soft Skills & Competencies

• Strong analytical and problem-solving skills.
• Ability to understand existing systems and translate requirements into working solutions.
• Clear communication with technical and non-technical stakeholders.
• Detail-oriented with a focus on reliability and maintainability.
• Comfortable working across multiple teams and applications.

Job Description:

Combine AI/ML and Technology knowledge to implement highly scalable solutions to solve real-world problems in areas such as Generative AI, Personalization, Image Recognition, Speech Recognition, Natural Language Processing, Best Next Action, and Time Series predictions

• Build solutions from identifying business problems, to collecting training dataset, to analyzing data, to modeling, to validating and to delivering production grade solutions at scale.
• Research latest related academic papers and test nascent ideas which can potentially solve new business problems and enhance existing solutions.
• Responsible for developing and defining deployment strategies for production quality AI solutions in Cloud infrastructure at scale
• Drive both high-level and detailed technical designs and conduct design reviews as needed
• Responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, and CI/CD tool integration
• Provide technical mentorship to team members at junior levels
• Actively participate in business and technical discussions and forums

We're building an AI-powered research platform for institutional investors. Our platform turns vast amounts of market, alternative, and proprietary data into actionable intelligence — powered by AI agents that depend on clean, reliable, real-time data to do their job.

We need someone to own data. Not manage a team that does data. Own it — from finding the right sources, to getting them flowing, to making sure they stay healthy at scale.

Today we ingest from hundreds of sources. That number is growing fast. The sources are diverse: real-time market feeds, regulatory filings, news, social sentiment, alternative datasets, and proprietary client data. Some are free APIs. Some are $10K/month enterprise contracts. Some are clients pushing their own data into our platform. Every one of them is different, and most of them will break in ways you don't expect.

You'll evaluate vendors, negotiate deals, build integrations, monitor quality, track costs, and make the call on what's worth paying for. When something breaks at 2 AM, you'll know why before the alert finishes firing.

This is an end-to-end ownership role. No handoffs.

Responsibilities

• Build and maintain integrations with a large and growing number of external data sources — APIs, WebSockets, file drops, streams, scrapers, and formats you haven't seen yet
• Evaluate and compare data vendors across quality, reliability, coverage, cost, and terms of service
• Negotiate contracts and manage commercial relationships with data providers
• Design and operate high-throughput ingestion pipelines handling mixed workloads (real-time, near-real-time, batch, event-driven)
• Build monitoring that tells you — before anyone else — when data is late, wrong, incomplete, or drifting
• Manage data quality at scale: anomaly detection, cross-source validation, schema drift detection, gap filling
• Handle both structured data (time-series, tabular) and unstructured data (documents, text, images) with appropriate extraction and storage
• Track costs per source, usage per consumer, and ROI — recommend what to keep, upgrade, or cancel
• Build tooling that makes adding the next data source faster than the last one
• Use AI tools aggressively in your daily work — for code generation, testing, documentation, anomaly analysis, and anything else that makes you faster

Requirements

You've done this before:

• 5+ years building data pipelines that run in production, 24/7, with real SLAs
• Deep hands-on experience with SQL databases and time-series data
• Python as your primary language, comfortable with async programming
• You've integrated with dozens of external APIs and dealt with the reality of unreliable vendors, changing schemas, rate limits, and bad documentation
• You've built monitoring and alerting for data systems — not as an afterthought but as part of how you work

You think about the whole picture:

• You don't just connect to an API. You think about what happens when it goes down, when the schema changes, when the data is wrong, when the bill doubles
• You understand that data has a cost and a value, and not every source is worth keeping
• You've worked with data vendors commercially — contracts, pricing tiers, usage negotiations

You use AI daily:

• AI coding tools are part of your workflow today, not something you're curious about
• You can articulate specifically how AI makes you faster and where it doesn't help
• You'd be frustrated if you couldn't use AI in your work

Nice to have

• Experience with financial market data
• Experience with streaming systems (Kafka or similar) at scale
• Vector database or embedding pipeline experience
• Experience with unstructured data extraction (PDFs, documents, NLP)

Perks & Benefits

• Senior individual contributor role with full ownership of the data domain
• Direct access to leadership — no bureaucracy, fast decisions
• AI tools provided and encouraged across all work
• Remote-friendly, async-first
• Compensation commensurate with experience

As a Senior Data Engineer, you will be working on:

• Translate data requirements from business users into technical specifications.

• Collaborate with partner agency’s IT teams on technology stack, infrastructure and security alignment.

• Build out data product as part of a data team:

• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems.

• Day-to-day monitoring of databases and ETL systems, e.g., database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence; ensure maximum database uptime;

• Construct, test, and update useful and reusable data models based on data needs of end users.

• Design and build secure mechanisms for end users and systems to access data in data warehouse.

• Research, propose and develop new technologies and processes to improve agency data infrastructure.

• Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures. • Maintain data catalogue to document data assets, metadata and lineage.

• Implement data quality checks and validation processes to ensure data accuracy and consistency.

• Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data.

What we are looking for:

• A Bachelor’s Degree, preferably in Computer Science, Software Engineering, Information Technology, or related disciplines.

• Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage.

• Demonstrated ability in using cloud technologies such as AWS, Azure, and Google Cloud.

• Experience with Databricks.

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

• Experience with orchestration frameworks such as Airflow, Azure Data Factory.

• Proficiency in working with Python, Shell Scripts, and SQL.

Preferred requirements:

• Familiarity with building and using CI/CD pipelines.

• Familiarity with DevOps tools such as Docker, Git, Terraform.

• Experience with implementing technical processes to enforce data security, data quality, and data governance.

• Familiarity with government systems and government's policies relating to data governance, data management, data infrastructure, and data security.

• Experience in Climate and Weather domains will be an advantage.

Here’s a shorter, more attention-grabbing version:

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