Total 1,175 data entry job vacancies in Information Technology category

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).

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.

This will be a 2-years direct contract position.

Responsibilities

• Data science developments.
• Lead project scoping discussions.
• Translate complex business requirements into technical solutions.
• Design, implement, and optimise end-to-end ML/AI solutions with improved performance and scalability.
• Systematically benchmark and evaluate multiple approaches, applying advanced techniques to solve complex business problems.
• Architect scalable solutions using cloud-based services and best practices, and design and implement robust data pipelines and LLM/MLOps workflows that improve efficiency and reduce operational costs.
• Deploy models to production environments with comprehensive monitoring, alerting, and maintenance procedures.
• Champion responsible AI practices, proactively identifying and mitigating ethical and governance risks.
• Collaborate with peers and stakeholders to ensure tasks are executed effectively, addressing minor conflicts constructively and respectfully, and suggesting improvements that enhance team effectiveness.

Requirements

• Bachelor's degree or higher in Data Science, Computer Science, Statistics, Economics, Quantitative Social Science, or related disciplines. Minimum 2 years of relevant experience in data science and/or public sector.
• Able to business use cases into analytical problems and identifying appropriate data sources.

Proficient in

• Writing scripts for data preparation and analysis, using modern analysis tools and programming methodologies.
• cleaning, imputing, and correcting anomalies in the collected structured or unstructured data.
• Exploring and analysing datasets, applying probability and statistical methodologies and techniques to discover insights from the data.
• Building machine learning models to identify, recognise patterns, and make predictions.
• Design principles and use of visualisations to best convey the intended information.
• Developing data visualisation from standalone graphs and charts on to highly customised tools and apps while tightly integrated into the data systems for real time visualisation of information.
• Translating results from analysis of work into actionable recommendations for stakeholders.
• Communicating results and business impact from analysis work in a coherent data story for stakeholders.

Ethos Search Associates Pte. Ltd.

EA License No: 13C6655

EA Reg No: R1988580 Jacky Chong

Key Responsibilities

• Develop and implement data analytics solutions to convert raw structured and unstructured data into meaningful insights.
• Apply data mining, data modeling, machine learning, and natural language processing (NLP) techniques to solve business challenges.
• Design and maintain scalable data pipelines, ETL processes, and data platforms to ensure data quality, accessibility, and reliability.
• Build dynamic dashboards, reports, and visualizations to communicate key findings and support decision-making.
• Establish data governance frameworks, data standards, metadata management, and asset catalogs to improve data consistency and compliance.
• Collaborate with cross-functional stakeholders to deliver data-driven solutions and optimize business processes.
• Evaluate emerging AI technologies and implement innovative solutions that enhance operational efficiency and business performance.

Preferred Qualifications

• Master's degree or above in Computer Science, Data Science, Engineering, Statistics,  Business Analytics or a related field.
• Proven experience in Data Engineering, Data Analytics, Machine Learning, AI Applications, or Data Governance.
• Strong proficiency in SQL, Python, and data visualization tools such as Tableau or Power BI.
• Experience building ETL pipelines, data lakes, APIs, and large-scale data platforms.
• Solid understanding of machine learning, predictive analytics, data modeling, and NLP techniques.
• Excellent analytical, problem-solving, and stakeholder management skills.

Interested candidate please click "APPLY" to begin your job search journey.

We regret to inform that only shortlisted candidates will be notified.

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PERSOL Singapore Pte Ltd

•RCB No. 200007268E • EA License No. 01C4394

•Registration ID: Heah Sian Wei R23117518

JOB DESCRIPTION

Build your career with Jabil! We challenge and empower you to make most of your talents, working with outstanding colleagues from diverse backgrounds who share your drive and passion to make Jabil grow!

JOB SUMMARY

A data scientist is a statistical analyst who have working experience in the field of data science. Work with other data scientists, ML Ops team, R&D team, Business users’ team etc. in collecting, analyzing, interpret data sets and build AI/ML models to drive optimization and improvement of product development. As part of the company's AI/ML team member, data scientist is required to provide help in developing custom data models and algorithms to apply to data sets. Data scientist must also coordinate with different functional teams to implement AI/ML and monitor outcomes.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Lead/work with team members to lead AI/ML cases with proper planning and execution to deliver the cases and drive the efficiency for the Manufacturing.

• Conducts data analysis, or Works with related team to design or build dashboards using generative AI tools

• Works with engineering and data science teams to support model training, fine tuning, and deployment workflows, ensuring that machine learning and generative AI systems are properly integrated, monitored, and optimized based on business requirements.

• Identifies and analyzes patterns with machine learning models or Generative AI models etc. during AI/ML model training, and utilize those for inferencing.

• Educates the organization both from IT and the business perspectives people on new approaches, such as Generative AI, machine learning, AI computer Vision etc.

JOB QUALIFICATIONS & KNOWLEDGE REQUIREMENTS

• Proficient in Python/R, Cloud techniques development experience is plus

• Strong statistics knowledge

• Familiar with regression models (i.e., xgboosting, lightGBM etc.), classification models (i.e., logistic regression, SVM, etc.), cluster models are preferred

• Familiar with Natural Language Processing (NLP) or Generative AI models

• Good data sensitivity skill set is plus

• Strong written and verbal communication skills and the ability to work effectively in teams and under pressure. Multi-lingual capability is a plus

• Highly motivated and creative, thinking “out of the box”

• Strong team mentality, interpersonal and communications skills

• Enthusiasm and ability to seek out and learn new technologies and algorithms outside of your immediate toolset/knowledge to solve business problems where required

EDUCATIONAL BACKGROUND & EXPERIENCE

• People who are taking his/her Bachelor or above degree in Computer Science, Machine Learning, Mathematics or Statistics

• 6 years or above experience of data mining/machine learning experience is preferred

• 3 years or above experience of Generative AI experience is preferred

• 1 years or above experience of AI computer vision experience is plus

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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Your new company

Our client in public sector is looking for an experienced Data Science Manager to join their team.

Your new role

• Translate strategic direction into actionable ML/AI digital transformation plans, ensuring scalable architecture and responsible AI standards.
• Define and drive CIO Office outcomes and OKRs, aligning with HQ goals and executing long-term roadmaps.
• Identify inefficiencies, anticipate risks, and take decisive action to improve operations and seize opportunities.
• Build cross-functional partnerships and foster a culture of innovation, collaboration, and continuous improvement.
• Develop and manage high-performing teams through coaching, hiring, and creating an environment for sustained performance.

What you'll need to succeed

• Bachelor’s or Master’s degree in Computer Science, Statistics, AI, or related quantitative field.
• Deep expertise in satellite data, cloud infrastructure, and government security requirements.
• 10+ years of technical leadership experience in data analytics, database management, and software development.
• Knowledge of space systems such as mission control software, orbital analysis, and space weather tools (preferred).
• Excellent communication and strategic thinking skills, with the ability to translate complex concepts into actionable plans, plus program management experience.

What you'll get in return

In return, you'll be part of an organization that values its employees. You’ll be rewarded with:

• Structured career growth and plenty of developmental opportunities
• Hybrid and stable working environment

What you need to do now

If you're interested in this role, click 'apply now' or for more information and a confidential discussion on this role or to find out about more opportunities in Technology, contact Yuki Cheung or email yuki.cheung@hays.com.sg. Referrals are welcome.

At Hays, we value diversity and are passionate about placing people in a role where they can flourish and succeed. We actively encourage people from diverse backgrounds to apply.

EA Reg Number: R22110258 | EA License Number: 07C3924 | Company Registration No: 200609504D

Job Overview

We are seeking an experienced Senior Data Engineer with strong expertise in enterprise Data Warehousing, Big Data platforms, Data Lake architectures, and modern cloud technologies. The ideal candidate will have hands-on experience designing and implementing large-scale ETL/ELT pipelines, data transformation frameworks, and analytics solutions within banking, financial services, or large enterprise environments.

The role requires deep technical knowledge of Apache Spark, PySpark, Hadoop ecosystems, Teradata, Cloud Data Platforms, and emerging Generative AI technologies for intelligent data processing and automation. The candidate should be capable of driving end-to-end data engineering initiatives, supporting business intelligence, analytics, regulatory reporting, and AI-enabled data solutions.

Key Responsibilities

• Design, develop, and optimize enterprise Data Warehouse and Data Lake solutions.
• Build scalable ETL/ELT pipelines using Python, Spark, and PySpark.
• Develop and maintain data ingestion, transformation, and analytical data processing frameworks.
• Implement data integration solutions across structured, semi-structured, and unstructured data sources.
• Manage large-scale data platforms using Hadoop, AWS S3, Azure Databricks, and Cloud Data Services.
• Develop data marts and business intelligence datasets for analytics and reporting.
• Implement metadata management, data lineage, and governance frameworks using tools such as Collibra and Enterprise Data Catalog.
• Design and optimize Spark SQL workloads for high-performance analytics.
• Build automated workflow orchestration solutions using Airflow, Control-M, or equivalent scheduling platforms.
• Integrate Generative AI capabilities into data engineering workflows for metadata tagging, data classification, anomaly detection, and intelligent reporting.
• Collaborate with business stakeholders, architects, data scientists, and analytics teams to deliver scalable data solutions.
• Ensure data quality, governance, security, and compliance requirements are met.
• Support production systems, troubleshoot performance issues, and maintain SLA compliance.

Required Skills

Data Engineering

• Apache Spark
• PySpark
• Spark SQL
• Python
• SQL / PL-SQL
• Hadoop HDFS
• Data Warehouse Design
• Data Lake Architecture
• ETL / ELT Development
• Dimensional Modeling
• Star Schema & Snowflake Schema

Cloud & Big Data

• AWS S3
• Azure Databricks
• GCP BigQuery
• Cloudera Data Platform
• Kafka
• Parquet
• Alluxio

Data Governance

• Collibra
• Enterprise Data Catalog (EDC)
• Metadata Management
• Data Lineage
• Data Quality Management

DevOps & Automation

• Airflow
• Control-M
• Jenkins
• GitLab
• Bitbucket
• CI/CD Pipelines

Generative AI

• OpenAI API
• Claude API
• LangChain
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Vector Databases (Pinecone, ChromaDB)

Preferred Experience

• 10+ years of Data Engineering experience.
• Banking, Financial Services, or Insurance domain experience.
• Experience working with Teradata Data Warehouses.
• Hands-on experience in Data Lake modernization initiatives.
• Experience delivering regulatory reporting and compliance data solutions.
• Exposure to AI-enabled data platforms and intelligent analytics solutions.
• Experience supporting enterprise-scale production environment

Responsibilities:

• Design and implement robust, scalable data pipelines and architectures to support data ingestion, processing, and storage. Including performance optimizations for data modeling and ingestion
• Develop and optimize complex SQL queries and stored procedures for data extraction, transformation, and analysis.
• Model data to meet different use casesng applications and automate data workflows.
• Collaborate with data scientists and analysts to understand data requirements and deliver high-quality data solutions.
• Lead the integration of data from various sources into data lakes and warehouses, ensuring data quality and consistency.
• Monitor and troubleshoot data pipelines and workflows to ensure optimal performance and reliability.
• Communicate with and support data users
• Document data processes, data models, and architectural designs to ensure knowledge sharing and compliance with best practices.

Prerequisites:

• Experience: Minimum 3 years in data engineering fields with system integration, and at least 1 year in system integration and implementation in cloud/web-based environments.
• Proven Solutions: Demonstrated experience in providing effective, working solutions and implementations, particularly in cloud-based environments.

Technical Skills:

• Solid understanding of ETL processes, data warehousing concepts, and data modeling best practices.
• Proficiency in Databricks, Azure Data lake, PowerBI, Tableau and related data processing and visualisation software.
• Familiarity with Windows, Linux, AWS and/or Azure platforms.
• Strong programming skills in languages such as Python and R is a must
• Proficiency in other programming languages such as Java, Scala and C# will be advantages
• Experience in data processing frameworks (e.g., Apache Spark, Apache Flink)

Preferred Exposure:

• Experience with large-data management system with visualisation tools.
• Experience with Data Integration and ETL Pipelines, Data Warehousing and BI reporting projects.
• Experience with Singapore Government Project will be advantages

Personal Attributes:

• Excellent problem-solving skills
• Ability to work independently
• Collaborative in a fast-paced environment

Why Join Us?
Be part of a forward-thinking team that is transforming government digital services. If you are passionate about technology and innovation, and thrive in a dynamic environment, we want to hear from you!

If you are passionate about building partnerships and driving growth, we would love to hear from you!

TOPPAN Ecquaria is an equal opportunity employer and values diversity within our company. We welcome all interested candidates to apply for this position, however, we regret to inform that only shortlisted candidates will be contacted by us for an interview.

Find us at www.topppanecquaria.com or www.linkedin.com/company/toppan-ecquaria

For more career opportunities, please visit our career site at:- https://toppanecquaria.com/careers/job-openings?utm_source=Jobstreet&utm_medium=Page&utm_campaign=2020 (Please copy & paste the above link onto your browser)

Keyrus is an international consulting firm, specializing in the integration of data intelligence and Digital solutions. With over 4000 employees spread across 27 countries, Keyrus continues to deliver on such projects to a wide range of clients from various industries including but not limited to Banking/Finance, Healthcare/pharmaceuticals, FMCG, Oil & Gas, and more.

As part of Keyrus’ solution delivery, we are also in a position to recruit and place technical consultants to complement on existing client projects with their expertise. As such, we seek innovative and agile people to support ambitious and forthcoming technological challenges.

About the Role

We are looking for a Data Analyst Consultant to support data-driven decision-making by transforming business data into meaningful insights. The successful candidate will work closely with stakeholders to develop reports, dashboards, and analytical solutions that support business and operational objectives.

Key Responsibilities

• Gather, analyze, and interpret data from multiple sources to identify trends and business insights.
• Develop and maintain dashboards, reports, and visualizations using Power BI or similar BI tools.
• Collaborate with business stakeholders to understand reporting and analytics requirements.
• Perform data validation and quality checks to ensure accuracy and consistency.
• Support ad-hoc analysis and provide actionable recommendations to business teams.
• Work closely with data engineering and technology teams to improve data availability and reporting capabilities.

Requirements

• 2–3 years of experience in Data Analytics, Business Intelligence, or a related field.
• Strong SQL skills and experience querying large datasets.
• Hands-on experience with Power BI
• Proficiency in Excel and data analysis techniques.
• Strong analytical, problem-solving, and communication skills.
• Experience translating business requirements into dashboards and reports.

Nice to Have

• Experience with Python for data analysis and automation.
• Exposure to Databricks, Azure, or cloud-based data platforms.
• Knowledge of data modelling and data warehousing concepts.
• Experience working with financial services, aviation, or asset-intensive industries.

• 3+ years of experience as a Data Analyst, BI Analyst, Reporting Analyst, or similar role.

• Strong analytical skills and ability to work with complex datasets.

• Good SQL skills for querying, validating, and analysing data.

• Experience with reporting and dashboard tools such as Power BI, Tableau, Qlik, or equivalent.

• Good understanding of data quality, data validation, metrics definition, and business rule documentation.

• Experience working with business users to clarify requirements and translate them into reports or dashboards.

• Familiarity with data models, reporting tables, and data pipelines is advantageous.

• Experience in enterprise, public sector, healthcare, or regulated environments is advantageous.

• Strong communication skills and ability to explain data clearly to both technical and non-technical stakeholders.

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.