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

Job Title: Big Data Development Engineer (Bachelor Fresh Graduate)

Department: Big Data Team

Stellarchip Technologies is a newly established startup dedicated to developing innovative semiconductor and data‑driven software solutions. As an emerging company, Stellarchip brings together expertise in chip‑level engineering and modern data analytics to help clients gain deeper insights, improve efficiency, and support digital transformation. The team is committed to exploring new technologies, experimenting with scalable architectures, and building high‑performance systems for real‑world applications.

As a brand-new startup committed to developing strong engineering talent, Stellarchip Technologies may provide opportunities such as:

• Short-term overseas technical training with partner companies or technology vendors
• On-site exposure to companies, especially those specializing in big data, cloud platforms, or semiconductor systems

Job Summary

We welcome bachelor’s degree graduates who have strong foundations in computer science and are passionate about backend development and big data technologies. You will participate in building and maintaining bigdata platforms, contribute to data processing workflows, and support system deployment.

Job Responsibilities

1. Backend Development (Top Priority)

• Participate in backend development of big data products using Java/Python.
• Assist in implementing data processing pipelines and simple algorithm components.

2. Big Data Projects (Important)

• Contribute to data modeling, ETL tasks, and distributed computation projects.
• Collaborate with senior engineers to analyze data and optimize workflows.

3. System Operations & Maintenance (General)

• Assist with deploying and upgrading big data software systems.
• Help monitor system health and performance using tools like Grafana or Prometheus.

4. Research & Documentation (Additional)

• Participate in technical exploration of new tools and frameworks.
• Prepare documentation for features, deployment steps, and design notes.

Qualifications

Education

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related STEM fields

Technical Skills

• Solid foundation in Java or Python
• Familiarity with data structures, algorithms, and computer systems
• Basic understanding of big data ecosystems (e.g., Hadoop, Spark, Hive, Kafka) — coursework or projects acceptable
• Exposure to Linux, SQL, Docker, or other engineering tools (bonus but not required)

Soft Skills

• Strong analytical and problem‑solving capabilities
• Passion for learning new technologies
• Good teamwork and communication skills
• Responsible and proactive attitude

Suitable for Candidates Who

• Are bachelor's fresh grads with strong CS fundamentals
• Have completed related academic projects or internships
• Want to grow into a big data backend engineer or data engineer role

Interested applicants may submit their resume to: info@stellarchiptech.com

Job Description

• Industry/ Organization Type: Cleaning/ Maintenance Services
• Position Title: Data Centre Cleaning & Maintenance Technician
• Working Location: Islandwide
• Working Hours: 6 days (Mon-Sat, 9am – 6pm)
• Salary Package: Basic + OT + Performance Bonus + Extra 2 days Leave/ month
• Duration: Permanent

Key Responsibilities

• Carry out cleaning tasks at assigned sites (e.g. vacuuming, mopping, disinfecting, etc.)
• Support installation works as instructed.
• Inform supervisors when supplies are low, equipment is damaged, or facility issues need repair.
• Assist with deliveries.
• Perform general housekeeping in the warehouse and storage areas.
• Follow safety and cleanliness requirements.
• Use cleaning and maintenance equipment safely and properly.
• Perform any other duties assigned by the Manager or Management.

APPLY NOW!!!

• Comfortable using cleaning tools and equipment.
• Willing to learn and adapt to different tasks and responsibilities.
• Basic English skills (able to read instructions and communicate).
• Willing to work overtime when needed, including after hours and weekends.
• Able to work well in a team and independently with minimal supervision.
• Good communication skills; responsible and reliable.

Kindly apply through ANY of the following methods:

• Submit your application by clicking the APPLY button;
• Email your resume to Job@anradus.com.sg. Please indicate #82315 on the email subject.

Anradus Application Policy: We value each application and ensure every resume is reviewed. Our process is efficient, typically concluding within 3 working days. If you do not receive communication from us within this timeframe, it's likely that your application has not been shortlisted by our client. In such cases, we recommend continuing your job search to maximize your opportunities.

Anradus Pte Ltd | EA License No. 20C0161 | Angel Lim | EA Reg No.: R1769781

The Junior Data Engineer will play a crucial role in building and maintaining the data foundations that support analytics,

reporting, and machine learning initiatives. This role is responsible for helping transform raw data from multiple sources into

reliable, high-quality, and business-ready datasets that enable better decision-making across the organization.

Working closely with data engineers, data analysts, and ML engineers, the Junior Data Engineer will support the

development of data pipelines, data quality processes, and monitoring practices in a cloud-based environment. This role is

ideal for someone eager to grow in data engineering, contribute to production-grade data solutions, and continuously learn

modern tools, processes, and best practices.

What you’ll be doing:

● Develop, maintain, and optimize ETL/ELT data pipelines using SQL and Python

● Collect and integrate data from multiple sources, including batch and near real-time systems

● Transform raw data into clean, validated, and business-ready datasets for analytics and machine learning use cases

● Implement data quality checks, validation, and QA processes to ensure data accuracy and reliability

● Write, test, and maintain SQL and Python code to support scalable and dependable data workflows

● Monitor data pipelines and assist in incident investigation, incident management, troubleshooting, and resolution

● Collaborate with data analysts, ML engineers, and other stakeholders to support evolving data requirements

● Contribute to documentation, knowledge sharing, and continuous improvement of data engineering practices

Technical Skills

• Basic experience with cloud platforms (GCP preferred)

• Working knowledge of SQL and Python

• Exposure to ETL/ELT concepts and data pipeline development

• Familiarity with version control (Git)

• Basic understanding of DevOps practices, such as:

CI/CD pipelines

Infrastructure as Code (e.g., Terraform)

● Awareness of agile software development methodologies

Operational Knowledge

● Familiarity with incident management concepts, such as monitoring,

alerting, and issue escalation in production systems

● Willingness to learn monitoring, alerting, and production support

practices

Soft Skills

● Clear and effective communication skills

● Ability to collaborate with cross-functional teams

● Adaptable and eager to learn new tools and technologies

● Good problem-solving mindset and attention to detail

Why join Angkas?

• Freedom of work
• Work-life balance
• Free meals and use of gym
• Opportunities for promotion
• Competitive salary
• Pay raise
• Start-up environment
• Multi-cultural and Agile work environment
• Diversified use of technology

About Innowave Tech Singapore
Innowave Tech is an Artificial Intelligence (AI) company offering solutions for the Semiconductor and Advanced Manufacturing industry. Utilizing deep industrial domain knowledge, proven experience, and innovation, we provide expert AI solutions and systems to address various industry pain points.

Roles & Responsibilities
We are seeking a Data Scientist with an interest in data analytics, insight generation, and optimization for manufacturing data. In this role, you will work independently alongside senior data scientists to analyze manufacturing datasets involving time-series sensor data, develop statistical analysis, and explore AI/ML.

Your Role and Impact
This role will focus on analyzing complex manufacturing datasets, developing predictive models, and implementing solutions for customers.

What You’ll Do

1. Data Analytics & Insight Generation.

2. AI/ML Modeling.

3. Collaboration & Deployment.
   

What We’re Looking For

* Educational Background:

Minimum Poly, Bachelor’s, or Master’s degree in Data Science, Statistics, Computer Science, Operations Research, Applied Mathematics, Engineering, or a related field.

* Technical Expertise:

• Proficiency in Python.
• Solid understanding in statistical analysis and machine learning/deep learning frameworks (Scikit-learn, LightGBM, XGBoost, TensorFlow, PyTorch).
• Experience in data visualization (Plotly, Seaborn, etc.).
• Knowledge in software engineering best practices (modularity, version control, testing).

* Soft Skills:

• Ability to work in cross-functional teams and communicate insights effectively.
• Strong problem-solving mindset and attention to detail.
• Self-motivated learner who quickly adapts to new tools and technologies.

* Bonus Skills:

• Knowledge of IoT data and manufacturing processes.
• Experience in deploying models.
• Experience with LLM (prompt engineering, RAG).

The Data Engineer is responsible fordesigning, building, and maintaining data infrastructure that supportsanalytics, applications, and enterprise reporting needs. This includesconstructing scalable pipelines, managing data flows across systems, andenabling reliable storage, integration, and retrieval of information acrosscloud and on‑premise environments. The role involves close collaboration withcross‑functional teams to deliver data‑driven solutions that are robust, secure,and high-performing.

Key Responsibilities

1. Data Architecture & Development

• Design, create, and deploy data models, tables, views, and data marts across data warehouses, operational data stores, data lakes, and data virtualization environments.
• Build backend APIs and database structures to support applications and data products.

2. Data Extraction & Transformation

• Perform data extraction, cleansing, transformation, and blending across multiple sources.
• Conduct web scraping activities when needed, using appropriate automation tools.
• Ensure data reliability, accuracy, and consistency through well-structured data processing workflows.

3. Data Pipelines & Processing

• Develop and maintain large-scale batch and real-time data pipelines using modern data engineering frameworks.
• Implement ETL/ELT processes leveraging tools such as SSIS, AWS Glue, AWS DMS, Python, Lambda, ECS tasks, EventBridge, Spring, or similar technologies.
• Integrate data from distributed systems and eliminate data silos through scalable and secure data flows.

4. Collaboration & Product Delivery

• Partner with Project Managers, Data Architects, Business Analysts, Frontend Developers, Designers, and Data Analysts to deliver end-to-end data-driven solutions.
• Participate in Agile ceremonies and contribute to continuous integration and delivery practices.
• Engage in pair programming and participate in code reviews to ensure coding standards and quality.

5. Infrastructure, Cloud & Big Data

• Work with cloud platforms such as AWS, Azure, or Google Cloud to build and operate cloud-native data solutions.
• Design and manage data pipelines in big data environments using tools like Spark, Hadoop, Kafka, RabbitMQ, or similar technologies.
• Ensure systems are resilient, scalable, and suitable for production workloads.

6. Data Governance & Security

• Apply data governance principles, ensuring compliant access, secure storage, and proper data handling practices.
• Implement security best practices for data assets and support policy enforcement across systems.

Required Technical Skills

Data Processing & Programming

• Proficient in data cleaning and transformation using SQL, Python (pandas), R, or equivalent tools.
• Strong skills in ETL/ELT pipeline development and workflow orchestration.

Databases & Storage

• Hands-on experience designing and operating relational and non-relational databases such as SQL Server, PostgreSQL, MySQL, MongoDB, Cassandra, Athena, SQLite, VoltDB, or S3-based storage.
• Familiarity with data warehouse, data lake, data mart, and data virtualization concepts.

System Design & APIs

• Solid understanding of system design, data structures, algorithms, and backend development.
• Comfortable working with REST APIs, HTTP protocols, and integrating various data sources.

Big Data & Distributed Systems

• Knowledge of distributed systems and tools (Hadoop, Spark, Kafka, etc.).
• Ability to implement streaming, micro‑batch, or batch processing pipelines.

Web Scraping & Automation

• Experience with web scraping technologies like BeautifulSoup, Selenium, CasperJS, PhantomJS, Node.js, or similar tools.

Security & Data Governance

• Familiar with access control, encryption, audit logging, and other data security practices.

Tools & Environment

• Comfortable working in both Windows and Linux environments.
• Experience using CI/CD pipelines and participating in DevOps-oriented workflows.

Soft Skills & Attributes

• Detail‑oriented with a strong focus on problem solving and analytical thinking.
• Good communication skills, capable of discussing technical topics with both technical and non‑technical stakeholders.
• Collaborative mindset and ability to work as a bridge between engineering and analytics teams.
• Self‑motivated, adaptable, and comfortable managing work in a fast-paced Agile environment.

Please submit resumes to john@oaktree.com.sg with the following details in MS Word format:

- Position applying for

- Current remuneration

- Expected remuneration

- Notice period

John Goh Meng Chye

EA License No : 06C4642

EA Reg No : R1102621

We regret that only shortlisted candidates will be notified.

Join our exciting team as a Data Engineer with the following job scope:

• Architect and implement data solutions on our large-scale data platform Hadoop using PySpark.
• Write complex and efficient SQL queries to extract and transform data from various sources.
• Design, build, and maintain scalable and reliable data pipelines using tools like Apache Airflow and Kafka.
• Develop and optimize data processing jobs on the Microsoft Azure cloud platform, leveraging services such as Azure Data Lake, Databricks, and Azure Data Factory.
• Collaborate with data analysts and other stakeholders to understand data requirements and deliver high-quality data products.
• Ensure data quality and integrity across all systems.
• Monitor, troubleshoot, and optimize the performance of our data infrastructure.
• Stay up-to-date with the latest trends and technologies in the Big Data space.

Key Responsibilities

Special Projects Leadership

• Lead high-impact, cross-functional projects spanning air network scheduling, airline partner planning, and operational performance.
• Act as a strategic advisor to planning leadership, identifying opportunities for innovation, efficiency gains, and capability enhancement.
• Drive end-to-end project execution from concept through deployment and adoption.

Advanced Analytics & Optimization

• Develop and implement optimization models and analytical frameworks to improve network design, scheduling efficiency, and partner performance.
• Apply data-driven approaches to solve complex planning problems, including routing, capacity allocation, and operational trade-offs.
• Translate analytical outputs into actionable insights for planning teams and leadership.

Automation & Tool Development

• Design, build, and maintain automation tools, scripts, and lightweight products to streamline planning workflows and reduce manual effort.
• Develop scalable solutions that integrate with existing scheduling and planning systems.
• Continuously identify opportunities to eliminate inefficiencies through automation and process redesign.

Cross-Functional Enablement

• Work closely with scheduling engineers, network planning engineers, operations teams, and partner management to embed solutions into daily workflows.
• Adapt tools and approaches to suit a wide range of users, from highly technical to operational planners.
• Provide hands-on support to ensure successful implementation and adoption of new tools and processes.

Experimentation & Innovation

• Lead experimental initiatives focused on advanced automation, optimization techniques, and emerging technologies.
• Pilot new approaches, evaluate outcomes, and scale successful solutions across the organization.
• Stay current with industry trends and best practices in airline planning, logistics optimization, and data analytics.

Standards & Best Practices

• Establish best practices for data usage, model development, and automation within the planning team.
• Ensure solutions are robust, maintainable, and aligned with operational realities.
• Document tools, methodologies, and processes to support long-term sustainability.

Minimum Qualifications

• Bachelor’s degree in Engineering, Data Science, Operations Research, Aviation, or related field, or equivalent experience.
• Significant experience in data analysis, analytics engineering, or operational analytics roles.
• Experience in airline scheduling, air network planning, or aviation/logistics operations.
• Demonstrated experience building automation tools, analytical models, or internal products (e.g., scripting, dashboards, optimization tools).
• Strong problem-solving skills with the ability to work across both technical and operational domains.

Preferred Qualifications

• Experience in air cargo operations or express logistics networks.
• Exposure to optimization techniques (e.g., linear programming, simulation, network optimization).
• Experience integrating tools with planning or scheduling systems.
• Some familiarity with data engineering, APIs, or system integration concepts.
• Experience leading cross-functional or innovation-focused projects.

Key Competencies

• Advanced analytical and problem-solving capability
• Automation and tool development
• Aviation and network planning domain knowledge
• Cross-functional leadership and influence
• Practical, solution-oriented mindset
• Adaptability and ability to work with diverse stakeholders
• Strong attention to detail and execution discipline
• Innovation and continuous improvement mindset

• Plan and execute marketing initiatives for AI data center and immersion cooling solutions.
• Create professional content: presentations, solution briefs, case studies, and digital/LinkedIn materials.
• Drive local campaigns, webinars, and events to generate leads and strengthen client engagement.
• Collaborate closely with sales and technical teams to develop customer-facing materials and proposals.
• Represent the company professionally at client meetings and industry events.

Requirements:

• Degree in Engineering, IT, Marketing, Business, or equivalent
• At least 5 years of B2B marketing experience in data centers, IT infrastructure, AI/GPU platforms, or cooling solutions.
• Solid understanding of data center operations, rack layouts, cooling technologies, and GPU-based AI systems.
• Ability to translate technical concepts into clear value propositions for non-technical stakeholders.

If you are keen to apply for the position, kindly email your detailed resume in MS Word to hr@recruit-expert.com

Please note that only shortlisted candidates will be notified.

For more job opportunities, please visit our website at www.recruit-expert.com

EA Licence: 19C9701

Registration: R1326740

Role Overview

Our client is looking for a skilled and motivated Data Engineer to join the Data & Analytics team. In this role, you will be responsible for designing, developing, and maintaining robust end-to-end data pipelines that power our operational and analytical capabilities.

You will work closely with data analysts, BI developers, data scientists, and business stakeholders to deliver high-quality, reliable data solutions at scale.

Key Responsibilities

Data Pipeline Engineering

• Design, develop, and maintain end-to-end data pipelines for ingesting, transforming, and delivering data from multiple source systems (databases, files, APIs, streaming platforms).

• Build and optimize ETL/ELT workflows using SQL, Python, and enterprise data integration tools.

• Ensure data pipelines are scalable, resilient, and performant to meet operational and analytical requirements.

Database & Data Platform Management

• Work hands-on with RDBMS platforms such as Oracle, DB2, SQL Server, or PostgreSQL for data extraction, transformation, and performance tuning.

• Develop and optimize SQL queries, views, and stored procedures to support reporting and analytics use cases.

• Support data modelling activities (logical and physical) for analytics and reporting layers.

Data Quality, Governance & Operations

• Implement data validation, reconciliation, and monitoring to ensure data accuracy, completeness, and consistency.

• Support operational data activities, including incident investigation, root cause analysis, and remediation.

• Maintain clear documentation for data pipelines, schemas, and operational processes to support audits and knowledge transfer.

Collaboration & Stakeholder Engagement

• Collaborate with business users, product owners, and downstream teams to gather requirements and translate them into technical solutions.

• Work closely with Data Analysts, BI developers, and Data Scientists to enable dashboards, reports, and advanced analytics.

Required Skills & Experience

• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

• Strong hands-on experience with SQL and relational databases (Oracle, DB2, SQL Server, PostgreSQL).

• Experience building and supporting ETL/data pipelines in enterprise environments.

• Solid understanding of data modelling, data quality, and data lifecycle management.

• Ability to troubleshoot data issues and work in production/operational environments.

• Proven experience with Python for data processing or automation.

Preferred / Nice-to-Have

• Experience with data streaming technologies such as Kafka, Apache Spark, or Apache NiFi.

• Familiarity with BI and visualisation tools such as Tableau, Qlik, or Power BI.

• Knowledge of cloud or hybrid data platforms and workflow orchestration tools (e.g. Airflow, Azure Data Factory).

. Knowledge of Agile/DevOps practices and CI/CD for data pipelines

About Innowave Tech Singapore

Innowave Tech is an Artificial Intelligence (AI) company offering solutions for the Semiconductor and Advanced Manufacturing industry. Utilizing deep industrial domain knowledge, proven experience, and innovation, we provide expert AI solutions and systems to address various industry pain points.

Roles & Responsibilities

We are seeking Senior Data Engineer to establish and lead our data infrastructure. The successful candidate will be responsible for building our data engineering practice from the ground up, implementing robust data systems for industrial AI applications, and establishing best practices that will power our semiconductor manufacturing AI solutions.

Your Role and Impact

As our first Senior Data Engineer, you will have a foundational role in building robust data infrastructure to handle manufacturing data and LLM applications, while establishing secure data practices that power our AI solutions for advanced manufacturing operations.

What You’ll Do

1. Select and manage on-premises technologies suitable for secure and efficient operations.
2. Build robust pipelines to collect, clean, and transform diverse datasets including process data, sensor data, image data, and human annotations.
3. Ensure secure, maintainable, and scalable deployment of data infrastructure.
4. Define and enforce best practices in data governance, privacy, and access control.
5. Collaboration & Deployment.

What We’re Looking For

Educational & Background:

• Minimum Poly or Bachelor Degree in Computer Science, Engineering, or a related field.
• Only Singaporean or Singapore PR can apply due to project requirement.

Technical Expertise:

• 3+ years of experience in data engineering roles, ideally with on-premises or hybrid infrastructure.
• Proven track record of building scalable data systems from ground up in a startup environment.
• Proficiency in Python and/or Java for data pipeline development.
• Solid experience with ETL frameworks (e.g., Apache Airflow, Dagster) and streaming systems (e.g., Kafka).
• Experience designing and maintaining SQL and NoSQL databases.
• Experience building and operating data lakes and data catalog.
• Familiarity with containerization (Docker), version control (Git), and CI/CD practices.

Soft Skills:

• Excellent communication skills and ability to collaborate with cross-functional technical and non-technical teams.
• Excellent problem-solving and debugging abilities.
• Ability to balance engineering tradeoffs.

Bonus Skills:

• Experience with manufacturing data systems, especially SPC, SCADA, and industrial sensor protocols (e.g., OPC UA, MQTT, Modbus).
• Familiarity with AI/ML pipelines and tools (e.g., MLflow).
• Knowledge in vector databases and LLM data infrastructure.
• Prior experience working in or with regulated industries (e.g., semiconductor, automotive, aerospace).

What we Offer

• A leading role in cutting-edge AI projects within the semiconductor industry.

• The opportunity to work with an learn from experts in the field of AI and data science.

• A dynamic, innovative, and supportive work environment.

• Competitive salary and benefits package.

• Career growth opportunities in a fast-paces technology company.

Role Summary:

We are seeking a hands-on Data Engineer to spearhead our Databricks Proof of Concept (POC) on AWS. You will be responsible for the initial environment setup, security configuration, and designing the framework for our future data platform. Working across diverse AWS and external data sources, you will build a unified, production-ready Databricks environment that validates the platform for broader adoption.

Key Responsibilities:

Platform & Infrastructure Setup

• Configure Databricks workspace integration with AWS (S3, IAM, VPC).
• Design and implement a scalable Medallion Architecture using Delta Lake (Bronze / Silver /Gold layers).
• Build automated ingestion pipelines leveraging Databricks Autoloader.

Data Engineering

• Cleanse and transform raw data from S3, RDS, and APIs into Delta tables.
• Optimize Spark jobs for performance, reliability, and cost-efficiency.
• Connect diverse AWS and external data sources into a unified Databricks environment.

Governance &Evaluation

• Establish data governance standards using Unity Catalog. (Good to have — not a hard requirement for the POC.)
• Configure Databricks Clusters with Autoscaling and Spot Instances to manage AWS spend.
• Define and evaluate POC success metrics covering performance, cost, and ease of use.
• Set up an end-to-end pipeline (Source → S3 → Databricks → BI Tool) within agreed timelines.

Qualifications and Experience:

Must-Have Skills

• Databricks Mastery — Expert knowledge of Delta Lake and Medallion Architecture (Bronze /Silver / Gold).
• PySpark / Spark SQL — Ability to write and optimize Spark code; Python strongly preferred over Scala or R.
• AWS Infrastructure — Deep understanding of S3 (bucket policies, storage), IAM(roles and policies) for secure Databricks access.
• Data Ingestion —Hands-on experience with Databricks Autoloader or Unity Catalog for managed data governance.
• 3–5+ years of professional experience in Data Engineering with PySpark / SQL.

Good to Have

• Networking — VPC configuration and AWS networking concepts.
• AWS Glue or Amazon EMR experience.
• Databricks Certified Data Engineer Professional certification.
• Experience connecting OOTB BI tools to Databricks environments.

Job Description

• Provide professional services to support the on-site build, configuration, and break-fix of Virtual Private Cloud (VPC) infrastructure in the Data Center.
• Escort engineers during on-site visits for hardware servicing and maintenance activities.
• Plan, schedule, and coordinate closely with OEM vendors for the physical installation, configuration, testing, and repair of server, storage, and network hardware.
• Ensure all hardware components—including servers, storage systems, and network devices—are mounted and installed according to design specifications.
• Follow up on cabling and patching requests to ensure proper connectivity and labeling.
• Collaborate with client teams and engineers to troubleshoot on-site hardware and infrastructure issues.
• Initiate and adhere to client change management and access control processes for all on-site activities.
• Provide physical hands-on support for server hardware, including power cycling, reboots, and component replacement.
• Other ad-hoc assigned duties.

Requirements

• Understanding of server hardware, SAN (Storage Area Network) storage, and networking components such as routers and switches.
• Proficient in server components including HDDs, CPUs, RAM, network interface cards (NICs), and storage controllers.
• Experience in Hypervisor VM Migration.
• Strong communication skills with the ability to collaborate effectively across multiple teams.
• Skilled in multitasking with a detail-oriented mindset and strong organizational abilities.
• Excellent troubleshooting skills for both hardware and network-related issues.
• Willing and able to work rotational shifts in a data center environment.
• Open to travel as required by job responsibilities.

The Data Scientist works closely with business stakeholders to uncover challenges, refine use cases, and design analytical solutions that drive measurable outcomes. This role spans the entire data science lifecycle—problem framing, data preparation, modelling, evaluation, communication of insights, and enabling adoption through compellingvisualizations and decision‑support tools.

Key Responsibilities

1. Problem Definition & StakeholderEngagement

• Facilitate discussions with business users to understand their pain points, clarify objectives, and convert them into analytically sound data science problem statements.
• Collaborate with stakeholders throughout the project to refine hypotheses, validate findings, and align on priorities.
• Manage expectations and timelines while balancing analytical depth with business needs.

2. Data Preparation & FeatureEngineering

• Conduct data cleaning, preprocessing, and transformation for both structured and unstructured data to ensure high data quality.
• Perform feature engineering to extract meaningful attributes that enhance model performance.
• Identify relevant datasets and integrate multiple data sources to support analytical work.

3. Analytical Modelling &Experimentation

• Explore data using statistical techniques to uncover trends, patterns, and relationships.
• Build machine learning models for prediction, classification, clustering, or other analytical tasks as required by the use case.
• Evaluate model performance and iterate based on stakeholder feedback and performance metrics.

4. Insights Delivery & Communication

• Translate analytical results into actionable recommendations that stakeholders can apply to drive decisions or business improvements.
• Develop clear, compelling narratives that explain insights and model behaviours in an accessible manner.
• Present analysis with well‑designed visuals, dashboards, and interactive tools that support storytelling and data exploration.

5. Visualisation & User‑Facing Tools

• Design dashboards and interactive visualizations to facilitate self‑service analytics and real‑time data monitoring.
• Apply strong visualization principles to ensure insights are intuitive and impactful.
• Build and deploy customised visual interfaces tightly integrated with underlying data systems.

6. Deployment, Monitoring &Continuous Improvement

• Support model deployment into production environments and collaborate with engineering teams to operationalize models.
• Monitor model performance over time and recommend enhancements as required.
• Contribute to agile project workstreams and participate in ceremonies such as stand‑ups, reviews, and retrospectives.

Required Skills & Competencies

Analytical & Technical Skills

• Ability to convert business challenges into analytical questions and identify appropriate data sources.
• Proficiency in writing data preparation and analysis scripts using tools such as Python, R, SQL, pandas, or equivalent.
• Strong foundation in descriptive statistics, probability, data exploration, and hypothesis testing.
• Skilled in building and validating machine learning models, using modern techniques and frameworks.
• Solid understanding of system design concepts, data structures, and algorithms.

Data Visualization & Storytelling

• Strong command of data visualization principles and tools.
• Capable of developing dashboards and interactive visual tools (e.g., using Tableau, Power BI, Plotly, or custom frameworks).
• Ability to communicate analytical insights through structured storytelling tailored for decision‑makers.

Data Engineering Familiarity

• Understanding of data modelling, data access patterns, and data storage structures such as data lakes, data marts, and data warehouses.
• Familiarity with REST APIs, web protocols, and data extraction via web scraping technologies.
• Comfortable working with big data frameworks (e.g., Spark, Hadoop, Kafka) when required for large-scale processing.

Soft Skills

• Strong communication skills, both written and verbal, with the ability to influence non‑technical audiences.
• Effective stakeholder management and experience working in iterative cycles with feedback loops.
• Organized, self-driven, and able to manage multiple priorities in an agile environment.

Experience Requirements

• Proven experience conducting end‑to‑end data science projects—from scoping and data preparation to modelling and deployment.
• Experience collaborating with diverse teams and managing stakeholders across business and technical functions.
• Prior experience in agile project management or participating in agile delivery teams.

Qualifications

• Degree or equivalent experience in Data Science, Statistics, Computer Science, Engineering, Mathematics, Information Systems, or related fields.
• Experience with production‑grade machine learning workflows is an advantage.

Please send your details in MS Word format to john@oaktree.com.sg:

- Position applying for

- Current remuneration

- Expected remuneration

- Notice period

John Goh Meng Chye

EA License No : 06C4642

EA Reg No : R1102621

We regret that only shortlisted candidates will be notified.

Avensys is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed services. Given our decade of success, we have evolved to become one of the top trusted providers in Singapore and service a client base across banking and financial services, insurance, information technology, healthcare, retail and supply chain.

We are currently looking to hire a Data Platform Engineer. This is an exciting opportunity to expand your skill set, achieve job satisfaction and work-life balance. More details as below.

ROLES AND RESPONSIBILITIES

• Design, develop, and maintained to end data pipelines for ingesting, transforming, and delivering data from multiple source systems (databases, files, APIs, streaming platforms).
• Build and optimize ETL / ELT workflows using SQL, Python, and enterprise data integration tools.
• Ensure data pipelines are scalable, resilient, and performant to meet operational and analytical requirements.
• Database & Data Platform Management
• Work hands on with RDBMS platforms such as Oracle, DB2, SQL Server, orPostgreSQL for data extraction, transformation, and performance tuning.
• Develop and optimize SQL queries, views, and stored procedures to supportreporting and analytics use cases.
• Support data modelling activities (logical and physical) for analytics and reporting layers.
• Data Quality, Governance & Operations
• Implement data validation, reconciliation, and monitoring to ensure data accuracy, completeness, and consistency.
• Support operational data activities, including incident investigation, root cause analysis, and remediation.
• Maintain clear documentation for data pipelines, schemas, and operational processes to support audits and knowledge transfer.
• Collaboration & Stakeholder Engagement
• Collaborate with business users, product owners, and downstream teams to gather requirements and translate them into technical solutions.
• Work closely with Data Analysts, BI developers, and Data Scientists to enable dashboards, reports, and advanced analytics.
• Participate in Agile ceremonies and contribute to sprint planning, estimation, and delivery

REQUIREMENTS

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• Strong hands on experience with SQL and relational databases (Oracle, DB2,SQL Server, PostgreSQL).
• Experience building and supporting ETL / data pipelines in enterprise environments.
• Solid understanding of data modelling, data quality, and data lifecycle management.
• Ability to troubleshoot data issues and work in production / operational environments.
• Experience with Python for data processing or automation.
• Experience with data streaming technologies (e.g. Kafka, Spark, NiFi).
• Experience with BI and visualization tools such as Tableau, Qlik, or PowerBI.
• Knowledge of cloud or hybrid data platforms and orchestration tools.
• Knowledge of Agile / DevOps practices and CI/CD for data pipelines.

WHAT’S ON OFFER

You will be remunerated with an excellent base salary and entitled to attractive company benefits. Additionally, you will get the opportunity to enjoy a fun and collaborative work environment, alongside a strong career progression.

To submit your application, please apply online or email your UPDATED CV in Microsoft Word format to keerthana@aven-sys.com. Your interest will be treated with strict confidentiality.

CONSULTANT DETAILS

Consultant Name: Keerthana Ramakrishnan
Avensys Consulting Pte Ltd
EA License 12C5759

Privacy Statement: Data collected will be used for recruitment purposes only. Personal data provided will be used strictly in accordance with the relevant data protection law and Avensys' privacy policy.