Total 89 data entry job vacancies in Information Technology category

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.

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.

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

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

As a Data Scientist (Smart Manufacturing and AI) at Micron, you will leverage advanced techniques from mathematics, statistics, and information technology to improve semiconductor product quality, yield, and productivity. You will develop predictive models, actionable insights, and AI-enabled solutions that address large-scale manufacturing and quality challenges involving die-level, wafer-level, test, and quality/customer-related data.

Your work will directly help prevent customer-impacting quality events, reduce escapes, accelerate root-cause analysis and corrective actions, detect distribution shifts in manufacturing and field signals, and enable intelligent automation across Micron’s global fabs, bridging factory learning with customer-facing product quality outcomes.

Responsibilities and Tasks

Product Quality (PQ) Predictive Solutions:

• Build and productionize ML models (classification/regression) for product-quality prediction (e.g., escape prevention, failure-mode prediction, risk scoring) across manufacturing and post-manufacturing data.

• Develop anomaly and drift detection/monitoring (e.g., Isolation Forest, autoencoders/VAEs) to identify emerging quality signatures in fab, test, and field/customer signals.

• Apply text analytics (embeddings, clustering, classification, summarization) to quality narratives, customer feedback, FA notes, and engineering logs.

Agentic AI Development:

• Contribute to the design and implementation of multi-agent systems for PQ workflows, including automated root-cause analysis and process optimization.

• Optimize for performance, latency, and token efficiency.

• Assist in implementing tool-using capabilities, function calling, and agent memory systems.

• RAG-LLM Development: Develop advanced retrieval strategies including hybrid search, re-ranking, and contextual compression.

Software Engineering and Productionalization:

• Develop robust, maintainable code and analytical pipelines suitable for high-volume manufacturing environments.

• Optimize system performance, latency, and token efficiency.

• Collaborate with senior team members on testing, deployment, and monitoring.

• Clearly communicate analytical insights, model behavior, and trade-offs to both technical and non-technical customers to enable data-driven decisions.

• Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.​

• Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.​

Required Qualifications & Skills

Education/Experience:

• Bachelor’s in Computer Science, Data Science, Operations Research, Mathematics, or a related highly quantitative field.

• Strong desire to grow a career as a Data Scientist in advanced, highly automated industrial manufacturing.

Technical Skills:

• Proficiency in Python and experience extracting and manipulating data using SQL.

• Solid foundation in statistics and machine learning (supervised/unsupervised learning, model evaluation, feature engineering).

• Experience with SQL for data extraction and manipulation.

• Experience with version control (Git).

• Familiarity with building interactive data applications or dashboards (e.g., Streamlit, PowerBI, or similar).

• Strong verbal and written communication skills, with the ability to explain complex analytical results clearly.

• Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes

Preferred Qualifications

• Exposure to LLMs, agentic AI frameworks, or RAG pipelines (internship experience, academic, or personal projects welcome).

• Experience with time-series data, process/manufacturing data, or handling concept drift/imbalanced datasets.

• Familiarity with cloud platforms (Google Cloud Platform, AWS, or Azure) and data visualization tools (Tableau, Power BI).

• Exposure to ETL tools, containerization (Docker), or web frameworks (Angular, React, FastAPI).

We are seeking an experienced Senior Data Analyst to lead the build and operationalisation of a robust data management platform across the region. This is a hands-on role suited for someone passionate about designing scalable data infrastructure and delivering reliable, production-grade data pipelines.

Experience with Microsoft Fabric is advantageous, but not required—candidates with strong data engineering fundamentals and a willingness to learn new technologies are encouraged to apply.

Data Platform & Pipeline Engineering

• Design, build, and optimise end-to-end data pipelines to ingest, process, and transform data from diverse regional.
• Develop scalable and maintainable data ingestion frameworks and processing patterns
• Establish a robust, high-performing data architecture to support analytics and downstream use cases

Data Management, Quality & Governance

• Embed data quality checks, validation rules, and monitoring within data pipelines
• Implement and support data governance practices including data lineage, metadata management, and access control (e.g., via tools like Microsoft Purview)
• Define and enforce data ownership, stewardship, and governance standards across the region
• Ensure compliance with internal policies and regional data regulations
• Collaborate with global data teams to align on governance frameworks, KPIs, and best practices

• Develop and maintain curated data layers and semantic models to support reporting and analytics needs

• Partner with business stakeholders to translate requirements into scalable data models
• Ensure consistency and standardisation of KPIs and reporting outputs across the region
• Support migration or integration of existing reporting platforms where relevant

Requirements/skills

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field
• Strong hands-on experience in building and managing data pipelines and data platforms
• Solid understanding of data modelling, data governance, and data quality best practices
• Exposure to cloud-based data platforms; familiarity with Microsoft Fabric or similar modern data platforms is a plus
• Proven ability to work in a fast-paced environment and adapt to new tools and technologies

EA License No. 01C4394

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About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.

About the role

We are seeking a Salesforce Data Analyst to support large-scale system integration projects involving Salesforce and multiple external systems.

You will start by assisting in data mapping and integration work between Salesforce and APIs (e.g. MuleSoft), gaining hands‑on exposure to how data flows across systems. This includes understanding Salesforce data models, integration payloads, and transformation logic.

You will also support testing activities (SIT/UAT) and work closely with experienced consultants across Salesforce, integration, and functional teams.

Over time, this role can evolve into a Business Analyst or Developer track, depending on project needs and your interests.

This role is suited for individuals who are detail-oriented, structured, and proactive, and who are interested in understanding how enterprise systems connect and operate end‑to‑end.

Responsibilities

Data Mapping & Integration Support

• Work closely with functional, integration (MuleSoft) and data migration teams to support end‑to‑end delivery.
• Assist in mapping data between Salesforce objects and external systems via APIs.
• Analyse field definitions, data structures, and relationships across systems.
• Support the documentation of data templates, mappings, transformation logic and integration requirements.
• Work with senior consultants to clarify data inconsistencies, edge cases, and validation rules.
• Review API payloads (JSON/XML) to understand how data is exchanged between systems.
• Perform data patching when required.
• Maintain clear and well-structured documentation such as data mapping sheets, integration specifications (functional level), test scenarios and results.

Requirements & Functional Support

• Support requirement discussions with business and functional teams to understand data-related needs.
• Assist in documenting simple user stories, process flows, and data-related requirements.
• Translate business requirements into structured data or integration-related inputs.

Testing & Quality Assurance

• Support requirement discussions with business and functional teams to understand data-related needs.
• Assist in documenting simple user stories, process flows, and data-related requirements.
• Translate business requirements into structured data or integration-related inputs.

Requirements

Must have skills and experience

• Interest in data, systems, or integration work.
• Strong attention to detail and ability to work with structured information.
• Ability to analyse and compare data across different sources.
• Good logical thinking and problem-solving skills.
• Able to follow through on tasks and track details consistently.
• Comfortable working with multiple teams and stakeholders.

Good to have

• Basic understanding of databases, data structures, or APIs.
• Familiarity with JSON, XML, or Excel-based data mapping.
• Exposure (academic or internship) to system integration, business analysis, or testing.
• Interest in Salesforce, cloud platforms, integration or enterprise systems.

Ways of working

• Work collaboratively within an agile, sprint-based build delivery environment.
• Learn by supporting senior consultants.
• Take ownership of assigned data mapping and testing tasks, ensuring accuracy and completeness.
• Communicate proactively on progress, issues, and dependencies.
• Be comfortable working with detailed, structured tasks that require consistency and attention.

Success measures

• Produce accurate and complete data mapping documentation with minimal supervision.
• Understand Salesforce data models and basic integration flows.
• Support testing cycles with minimal errors in data validation.
• Proactively follow up on issues and close assigned tasks.
• Communicate clearly and build working relationships across teams.
• Demonstrate reliability, attention to detail, and ownership in day‑to‑day work.

Education

• Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience

Let's talk about what's in it for you!

Passionate people are Capgemini's Ace of Spades - join us to discover a career that will challenge, support and inspire you. Working at Capgemini you'll find the rewards are more than just financial. You will work alongside some very smart and inspiring people on exciting projects and you will also enjoy incredible benefits. We offer flexible work practices and 40 hours of self-development every year with a huge selection of learning opportunities to choose from.

As "Architects of Positive Futures", Capgemini actively supports the community in 3 ways:

Diversity and Inclusion - we believe diversity of thought fuels excellence and innovation, which is why we positively encourage applications from suitably qualified candidates regardless of their gender identity, ethnicity, sexual orientation, religion, ability, intersex status or age. To support our commitment to diversity and inclusion, we celebrate special events and days of significance that are important to our employees such as Diwali, Bastille Day, Pride, IDAHOBIT, IWD and International day of people with Disabilities. Our Employee Resource Groups Women@Capgemini and OutFront support the grassroots passion of employees to drive our diversity agenda and effect change.

Digital inclusion - at Capgemini we are using our skills to drive social impact initiatives focusing on helping society address the impact of the digital and automation revolution. We also provide employees with opportunities to give back to the community through charity projects and volunteer days.

Environmental Sustainability - Capgemini joined the CDP's (Carbon Disclosure Project) prestigious "A list" for its commitment to the Net-Zero economy. We are focusing on helping our clients transform towards more sustainable business models and committing to reduce our own carbon emissions (GHG) by 20% per employee by 2020.

Recognised by Ethisphere as one of the World's Most Ethical Companies for the last 8 years in a row, ethics and values are at the heart of Capgemini's corporate culture and business. Embedded in our DNA, our seven values - Honesty, Boldness, Trust, Team Spirit, Freedom, Fun and Modesty - have remained the same since company inception in 1967. To see how we bring these values to life, click here to listen to some of our employee’s stories.

Come join us, bring your whole self to work, create new possibilities for you, your customers and your community and help us to be Architects of Positive Futures.

Data Analytics

• Spearhead the design and execution of end-to-end data analytics strategies.
• Develop and manage automated data pipelines and ETL workflows.
• Perform data cleaning, preprocessing, and validation to maintain high data accuracy and integrity.
• Utilize advanced statistical and data mining techniques to analyze extensive healthcare datasets.
• Build and maintain interactive dashboards with user-friendly visualizations tailored for non-technical stakeholders.
• Deliver in-depth analytics to support clinical research and quality improvement projects, especially in areas like chronic disease management (e.g., diabetes, kidney disease, asthma).
• Create predictive models and deploy machine learning solutions, including large language models (LLMs).
• Collaborate with clinical teams to integrate Patient-Reported Outcome Measures (PROMs) into existing care processes.
• Work closely with GTO and AIO teams to improve data visibility and accessibility.
• Design and apply LLM-based solutions to streamline and optimize patient care pathways.

Data Quality & Monitoring

• Conduct regular validation to ensure the integrity and consistency of datasets.
• Detect and interpret key trends, patterns, and insights from healthcare data.
• Establish and maintain robust data quality assurance and validation protocols.
• Generate and present clear, data-driven reports and visualizations to stakeholders.
• Ensure all data visualizations are user-centric and accessible to non-technical users.
• Liaise with cross-functional teams to gather and address their specific data requirements.

Data Governance & Protection

• Implement stringent data security policies and access controls.
• Supervise data standardization and quality management initiatives.
• Ensure adherence to data privacy laws such as PDPA and HBRA.
• Develop secure protocols for safe data exchange and collaborative access.
• Promote ethical AI usage and ensure responsible deployment of LLM technologies.

Key Requirements

• Bachelor’s degree in a quantitative field (e.g., Computer Science, Data Analytics, Statistics)
• Minimum of 2 years’ experience in healthcare analytics or a similar field.
• Strong programming skills in Python, R, and SQL.
• Hands-on experience with data visualization platforms such as Tableau, Power BI, or TIBCO Spotfire.
• Proficiency with cloud analytics environments, especially Databricks.
• Solid foundation in statistical methods, including predictive modeling, A/B testing, and time-series analysis.
• Skilled in deploying and fine-tuning AI/ML models, including LLMs, within healthcare contexts.
• Experience working with cloud providers, particularly AWS.
• Familiarity with container technologies like Docker and Kubernetes.
• Experience using modern web frameworks such as Streamlit, NextJS, and TypeScript.
• Proficient in REST API development using frameworks like FastAPI.
• Understanding of database design, with hands-on experience using tools like SQLAlchemy.
• Capable of working with large and complex datasets.
• Proficient in using Git for version control and collaborative coding.
• Strong grasp of CI/CD pipelines and DevSecOps best practices.
• Knowledge of medical terminology and healthcare IT systems.
• Demonstrated ability to manage stakeholders and drive successful project outcomes.
• Excellent analytical thinking and problem-solving capabilities.
• Effective communicator with strong presentation, writing, and interpersonal skills.
• Highly detail-oriented, with a commitment to accurate data handling and analysis.
• Able to convert business challenges into technical data solutions.
• Team-oriented, proactive, and capable of thriving under time constraints.
• Comfortable working both independently and collaboratively in dynamic environments.

To apply, please visit www.gmprecruit.com

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA License: 11C3793 | EA Personnel: Bautista Gia Grace De Guzman | Registration No: R23111973

• Possess a degree in Computer Science/Information Technology or related fields.
• Min 8 years of relevant working experience in software or data engineering with proficiency in Python.
• Strong experience in unit and integration testing.
• Familiarity with DevOps practices and Agile methodologies.
• Strong software engineering, analytical and problem-solving skills.
• Good team player and communication skill.
• CAT-1 cleared/eligible candidate is required for this role.
• Experience in AWS and Kubernetes (K8s)
• Familiarity with data platforms such as Snowflake, Apache Spark, or Apache Hive, as well as orchestration tools like Apache Airflow, Dagster, or Prefect.
• Familiarity with GitHub workflows and Datadog.
• Develop and maintain data pipelines and ETL/ELT processes, and ensuring maintainability through unit and integration testing.
• Collaborate with data teams to understand requirements and automate deployment and monitoring.
• Optimize data storage and troubleshoot issues to enhance performance.

The Data Center Operations Engineer is responsible for the daily operation, maintenance, and optimization of data center infrastructure, including electrical, HVAC, and ELV systems. This role ensures facility reliability, safety, and efficiency through proactive monitoring, risk management, and continuous improvement.

Perform daily operation, maintenance, and routine inspectionsprovement. The position requires hands-on technical ability, strong analytical skills, and strict adherence to operational and emergency procedures.

Perform daily operation, maintenance, and routine inspectionsprovement. The position requires hands-on technical ability, strong analytical skills, and strict adherence to operational and emergency procedures.

of data center electrical, HVAC, and ELV systems, ensuring stable and continuous operation.

Execute scheduled preventive maintenance (PM) plans and handle system faults promptly and accurately.

Conduct facility safety, risk, capacity, and availability management, continuously optimizing systems to improve operational efficiency and cost-effectiveness.

Maintain infrastructure data accuracy (100%), regularly check alarm configurations, and ensure monitoring platform stability and reliability.

Conduct facility inspections per company requirements, including equipment status checks, MOP (Method of Procedure) review, and maintenance tracking.

Respond rapidly to incidents and emergencies following EOP (Emergency Operation Procedures) and incident management standards; provide on-site support and reporting.

Analyze root causes of incidents, conduct post-event reviews, and summarize lessons learned for continuous improvement.

Familiarize with the power distribution, cooling, and ELV architecture within assigned data centers; quickly locate and resolve faults when issues occur.

Prepare and implement change MOPs independently, ensuring no incidents result from planned changes.

Participate in optimization and upgrade projects, ensuring smooth on-site execution and coordination.

Propose technical improvements or modification plans for infrastructure monitoring, capacity, safety, and availability.

Provide technical guidance, mentorship, and training for frontline operation staff.

Ensure quick response and arrival per incident management policy.

Strictly comply with all operational procedures, safety policies, and company regulations.

Complete other assignments as defined in the Service Contract, Outsourcing Specification, or as required by the company or project team.
Qualifications

Education: Full-time college diploma or above (Associate Degree or higher).

Major: Electrical Engineering, HVAC, or other related disciplines.

Experience: Minimum 3 years of relevant experience in data center facility operation and maintenance.

Strong understanding of data center infrastructure systems, including electrical distribution, cooling, ELV, and monitoring systems.

Familiar with mainstream facility brands and models, capable of identifying differences and proposing optimization suggestions.

Demonstrated ability to conduct root cause analysis and implement effective preventive actions.

Capable of independent MOP preparation and execution with zero error rate.

At Alcon, we are driven by the meaningful work we do to help people see brilliantly. We innovate boldly, champion progress, and act with speed as the global leader in eye care. Here, you’ll be recognized for your commitment and contributions and see your career like never before. Together, we go above and beyond to make an impact in the lives of our patients and customers. We foster an inclusive culture and are looking for diverse, talented people to join Alcon.

As a Data Scientist under Manufacturing Science & Technology (MS&T) Department, you will be primarily responsible for driving automation initiatives within the Manufacturing Science & Technology team by managing system changes, enhancements, and validations while ensuring compliance with project documentation and SOPs. Supports SMART manufacturing projects through data analysis, reporting tool administration, and system support to enable efficient, data-driven operations.

In this role, a typical day will include:

• Manage system change and related enhancement/bug fix, review project documentation and related SOPs and perform system validation
• Analyzes data to generate insights and predictions
• Maintain, support and administrate reporting tool and related applications.
• Lead and support SMART Manufacturing/Automation initiatives related projects. Develop/review project documentations and related SOPs.
• Perform system/software validation

WHAT YOU’LL BRING TO ALCON:

• Bachelor degree of related fields (computer science or equivalent)
• Proficient in any programming language is required for this role
• Minimum 3 - 5 years relevant working experience in IT software development lifecycle, system implementation and system maintenance and supports.
• Hands on knowledge on automation engineering, PLC/SCADA/MES systems, Microsoft SQL/Oracle/Access database/Python/R/Microsoft Visual Basic/C#/ASP.net programming and IT (Infrastructure and Network).
• Knowledge on 21 CFR Part 11 (computerized system validation) is preferred but not a MUST
• Training will be provided for those without experience

HOW YOU CAN THRIVE AT ALCON:

• Good team player
• Enjoy working with various cross functional team across manufacturing site

Alcon Careers

See your impact at alcon.com/careers

You will be responsible for the end-to-end softwaredevelopment and support for all work related to Enterprise Data Warehouse (EDW)projects, quarterly change requests, L3 production fixes. This includessoftware product implementation and administration, application design,development, implementation, testing and support. You will be expected to workon Data team.

You will also be responsible for quality assurance of the team’s delivery inconformance with the Bank-defined software delivery methodology and tools. Youwill partner with other technology functions to help deliver requiredtechnology solutions.

• Create frameworks, technical features which helps in faster operationalisation of Data models, Analytical models(including AI/ML) and user generated contents (dashboards, reports etc)
• Effectively partner with citizen data scientists in enabling faster adoption of AL/ML model based systems
• Independently install, customise and integrate software packages and programs
• Carry out POCs involving new data technologies
• Design and develop application frameworks for data integration
• Create technical documents such as solution design, program specifications for target solutions
• Perform design and development of applications which may not be limited to: Software Applications, Data Integration, User Interfaces, Automation Maintain and recommend software improvements to ensure a platform centric management of software applications
• Performance tuning
• Work with production support team members to conduct root cause analysis of issues, review new and existing code and/or perform unit testing
• Perform tasks as part of a cross functional development team using agile or other methodologies and utilising project management software

• Hands-on experience in implementing large scale data warehouse, Data mart & analytics platforms in financial services industry with good functional knowledge of products & services offered in Retail bank / Wholesale / Global Markets covering some of the following analytics domains:
• Experience in Data Modeling, Data mapping for Data Warehouse and Data Marts solutions
• Expertise in FSLM or similar industry models
• Expertise in Reference data management – Tools experience such as MDM (Master Data Management)
• Experience in functional domain - Retail , Wholesale, Compliance , Digital
• Experience in analytics - Retail Analytics
• Expertise in design of role based fine grained access control
• Designing cloud ready data solutions, Virtualization  

• Technical skillsets -ML Model operationalization, Building Data Pipelines and Hadoop based Data marts
• Expertise in implementing Big Data frameworks using multiple SQL engine such as Spark, Impala, Hive, etc
• Expertise in implementing Hadoop based Data mart using Spark based framework (Java, Scala, Pyspark)
• Leverage LLM model to build intelligent data applications (eg: Natural Language based SQL generation)
• Experience in end to end AI / ML life cycle (Data pipeline, model training, Model development, deployment, fine tuning, etc)
• Expertise in building Data federation solution(Trino, Presto, Dremio, Query Grid) along with Data caching / Indexing
• Experience in working with any of Data Catalog tools and Automating Data Quality checks using frameworks
• Good Working experience in core technical area using Python, Java, PySpark and Scala
• Expertise in Cloudera CDP components
• Good knowledge in developing Spark based ingestion framework (Java, Scala, Pyspark)
• Experience in building and operationalising feature pipeline to support AI/ML model execution, data pipelines for supporting large scale data warehouse/data marts

• Additional requirements - 2 to 3 technical certifications from enclosed list:
• Cloudera Hadoop distribution–Hive, Impala, Spark, Kudo, Kafka, Flume
• Teradata–Bteq, Query Grid, GCFR, MDM, TAS, Data Mover, BAR
• Informatica Data Integration – PC, IDR, BDM, MM, IDQ, EDC
• Data modelling tools (Erwin)
• QlikSense
• Microsoft – R
• Data science workbenches – Cloudera Machine Language, Jupyter, DataRobot, H2O.AI, IBM DSX
• Data Virtualization tool (Denodo, Dremio)
• AS400
• Language – SQL, Java, Python, Scala, Pyspark
• Automation / scripting – CtrlM, Shell Scripting, Groovy

About the Role
The Project Engineer will work closely with project leads, clients, vendors, and technicians to ensure smooth project execution from construction phase to data center handover.

Key Responsibilities

• He is responsible for monitoring, maintaining the Data Centre and coordinating the deployment, installation, and commissioning of data center infrastructure and IT systems, including power, cooling, fire suppression systems, and IT systems performance managing cabling works, server and network equipment setup, troubleshooting, and ensuring adherence to project timelines, quality standards, and safety requirements.
• He will need to manage end‑to‑end delivery of Data Centre projects, ensuring quality, safety, and compliance with local regulations.
• He will need to coordinate with internal teams, consultants and contractors to achieve project milestones and oversee project budgets, schedules and resources to ensure successful completion.
• After the completion of the projects, he will need to prepare project reports, documentation and updates for management and clients.
• He also needs to respond to alarms, faults, and emergency situations, and implement solution.

Requirements

• Diploma or Degree in Mechanical & Electrical Engineering, Building & Construction, or a related discipline.
• Min 4 years of Data Centre project experience is preferred and local project experience in Singapore is required.
• Strong hands-on technical capability on Data Centres, coupled with project planning and coordination skills.

• Prior hands-on experience in data center environments including rack & stack, cabling, patching, and hardware installation.
• Basic knowledge of data center cooling, airflow management, and power redundancy systems.
• Candidates with other mission‑critical or high‑spec project experience (e.g. hospitals, airports, large commercial builds) are welcome to apply.
• Ability to work in fast‑paced environments and deliver under tight deadlines.

• Some experience and knowledge of MEP equipment such as UPS, generator, Chiller, Pump, cooling tower is preferred