Key Responsibilities

• Process and prepare data files for printing (e.g., formatting, validation, sorting)
• Operate and monitor printing systems and related software
• Ensure accuracy and completeness of data before print production
• Troubleshoot basic system, file, or print issues
• Maintain logs and records of processed jobs
• Perform file conversions (e.g., PDF, CSV, print-ready formats)
• Coordinate with design, production, or customer teams as needed
• Adhere to data security and confidentiality standards
• Meet deadlines for high-volume print jobs
• Knowledge of PrintSoft and Excel will be added advantage.

Job Objectives

Analyze and translate business, regulatory, and analytics requirements into scalable data and solution designs. Drive effective stakeholder communication, effort estimation, and validation processes, while enabling data architectures and curation strategies that support reporting, analytics, and AI/NLP-driven use cases.

Key Responsibilities

• Perform detailed effort estimation for projects and change requests.
• Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner
• Review and approve test strategies, functional test cases, and data validation approaches.
• Experience translating business and compliance requirements into NLP‑enabled analytical use cases, such as: Text classification and categorization, Entity extraction, Risk indicator identification, Summarization of alerts, cases, or documents
• Ability to translate business, regulatory, and analytics requirements into logical data layering and curation strategies that support reporting, analytics, and AI/NLP use cases
• Analyze business and regulatory requirements and translate them into scalable solution designs.
• Perform detailed effort estimation for projects and change requests.
• Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner
• Review and approve test strategies, functional test cases, and data validation approaches.
• Ability to design data architectures supporting NLP and AI‑driven analytics, including ingestion, curation, and governance of unstructured data within Data Lake, Data warehouse platforms.
• Experience translating business and compliance requirements into NLP‑enabled analytical use cases, such as: Text classification and categorization, Entity extraction, Risk indicator identification, Summarization of alerts, cases, or documents
• Ability to translate business, regulatory, and analytics requirements into logical data layering and curation strategies that support reporting, analytics, and AI/NLP use cases

Key Skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
• Minimum of 9+ years of professional experience
• Requirement Analysis & Solution Design
• Data Architecture & Data Modeling
• AI / NLP Use Case Enablement
• Testing & Data Validation
• Stakeholder Communication
• Effort Estimation & Planning

Responsibilities:

• To support and deliver any activities which required 24x7
• To support Service Request, Incident and Change activities
• To support and deliver requested Daily Infra Operations activities
• To support and deliver requested Environment Operations activities
• To support and deliver requested task from Projects team
• To support and deliver requested task from IT Initiative Projects
• To support, coordinate, monitor and supervise any external vendor working in restricted facilities

Requirements:

• Minimum of 1-3 years hands-on experience in providing Data Center support
• Minimum 1-3 years of cabling experience (preferably structured cabling)
• Degree or diploma in IT would be an advantage
• Ability to work independently with minimal supervision
• Able to communicate messages clearly and concisely
• Ability to maintain high-quality performance and constantly deliver results in a timely manner

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Infrastructure Management

• Manage and maintain complex cloud environments for AI workloads.
• Ensure secure, stable connectivity between internal systems and AI platforms.
• Perform ongoing system maintenance and monitoring to guarantee optimal AI model performance.
• Implement and maintain security protocols for AI data handling and model deployment.

Rapid Prototyping & Technical Validation

• Conduct technical due diligence for new AI technologies, frameworks, and vendor solutions.
• Build proof-of-concepts to validate AI model feasibility and performance.
• Perform stress-testing of AI vendor APIs, model endpoints, and third-party integrations.
• Document technical findings and provide recommendations for AI technology adoption.

Pipeline Development & AI Infrastructure

• Develop and maintain automated data pipelines for AI model training and inference.
• Write robust code to ensure reliable data movement from source systems to AI models.
• Implement MLOps practices for model deployment, monitoring, and maintenance.
• Build and maintain AI model serving infrastructure and API endpoints.

Must-Have Requirements

• Bachelor’s degree in Computer Science, Data Science, AI/Machine Learning, or related technical field.
• 3+ years of experience in AI/ML engineering or related technical roles.
• Strong programming skills in Python, with experience in AI/ML libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with cloud infrastructure management (AWS, Azure, or GCP).
• Knowledge of MLOps practices, model deployment, and monitoring.
• Experience with API development and integration for AI services.
• Understanding of data pipeline tools and ETL processes for AI applications.

Responsibilities

1. Perform duty to manage data centre (DC)operations, maintenance, troubleshooting, project rollout and facilities related matters.

2. Perform DC monitoring and maintenance on infrastructure systems, critical facilities and associated equipment.

3. Perform preventive and corrective support to scheduled or unscheduled maintenance on DC

infrastructure systems, critical facilities equipment and/or services.

4. Ensure all subcontractors deliver a quality and competent service and all contractual obligations are met. Supervise the vendors to all scheduled and adhoc activities related to DC facilities.

5. Perform DC and critical facilities work on environmental and management programs

6. Perform equipment functionality test and data analysis

7. Perform assets management duty, includingmaintaining of inventory, change and control programs and purchase of parts and supplies

8. Promptly respond and attend to incident and/or emergency situations

9. Provide standby support upon activation for shift duty stand-in and/or other coverage

10. Conduct routine, sanity check and ongoing assessment of DCC infrastructure systems and critical facilities operations

Requirements:

• Nitec / Higher Nitec / Diploma in Electrical/Mechanical/DC Infrastructure or relevant engineering discipline (Electrical, Mechanical or related fields)
• Additional certifications relevant to the industry is an added advantage
• 1 -2 years experience maintaining electrical, mechanical, fire protection system in facility management, particularly handling critical systems would be an added plus
• Strong problem-solving abilities, communication skills, and the ability to work independently and as part of a team
• Proficient in Computer skills eg. microsoft office, google emails, docs etc

Junior Data Scientist – Business Operations & Analytics

Summary

We are seeking a highly analytical and strategic Junior Data Scientist to drive data-led decision making across a large-scale customer and business operations environment. This role will focus on leveraging advanced analytics, reporting, and data modelling to uncover actionable insights, improve operational performance, and influence business strategy. The ideal candidate thrives in ambiguous environments, can independently manage complex cross-functional initiatives, and is passionate about transforming data into meaningful business outcomes.

Responsibilities

• Develop and execute data science and analytics strategies that support business objectives and operational excellence.
• Design, build, and maintain advanced analytical models, prototypes, and frameworks to identify trends, opportunities, and performance improvements.
• Extract, process, and analyze large, complex datasets using SQL, Python, R, and Big Data technologies.
• Create and maintain scalable dashboards, reporting systems, KPIs, and operational metrics to support business performance monitoring.
• Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders.
• Partner closely with cross-functional teams including Operations, Product, Engineering, and Business Leadership to solve complex business challenges.
• Drive data governance, reporting best practices, and continuous improvements in analytics methodologies.
• Mentor and support analysts and data professionals, fostering a culture of collaboration, innovation, and analytical excellence.
• Identify opportunities to automate reporting, streamline workflows, and improve operational efficiency through data-driven solutions.
• Present insights and strategic recommendations to senior leadership to influence decision-making and business direction.

Requirements

Essential

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative discipline.
• 2 - 3 years of experience in data analytics, data science, business intelligence, operations analytics, or a similar function.
• Advanced SQL skills, including the ability to build, optimize, and maintain complex queries against large datasets.
• Experience working with Big Data technologies and analytical tools such as Tableau, Hive, Presto, Python, and/or R.
• Strong understanding of operational metrics, KPIs, reporting frameworks, and performance measurement methodologies.
• Proven ability to perform exploratory analysis and derive actionable insights from complex datasets.
• Experience designing dashboards, reports, and visualizations that support business decision-making.
• Excellent communication and stakeholder management skills, with the ability to explain technical concepts to diverse audiences.
• Strong problem-solving mindset with the ability to work independently in fast-paced and ambiguous environments.

Preferred

• Experience supporting Customer Operations, Customer Support, Scaled Operations, Shared Services, or Business Operations functions.
• Experience working with large-scale datasets in high-growth technology, digital, e-commerce, or platform-based organizations.
• Knowledge of data pipeline architecture, ETL processes, and data warehousing concepts.
• Exposure to machine learning, predictive analytics, forecasting, or statistical modelling techniques.
• Demonstrated track record of driving measurable business impact through data-driven initiatives.
• Experience mentoring analysts or leading cross-functional analytics projects.

This is an initial 12-months contract role

Our client, one of Asia-Pacific’s leading organizations is looking for:

Data Scientist

Responsibilities:

• Work with product owners, engineering teams, and industry partners throughout the product development lifecycle from concept, design, prototyping, acceptance testing, data curation, delivery, operationalisation, industry proliferation, to product end-of-life
• Develop and deploy software components based on microservices-based architecture
• Participate in agile secure software development processes and best practices, documentation of user requirements and software codes during the software development lifecycle
• Propose, implement, and validate algorithms, ensuring functional and non-functional requirements

Requirements:

• Degree in Engineering, Computer Science, Mathematics, Statistics or equivalent with strong technical knowledge in AI
• Good understanding of the latest research and technologies in AI for production deployment
• Strong coding experience in programming languages such as Python and/or C++
• Experience working with libraries for data manipulation, visualization, machine learning, and reporting.
• Hands-on experience with one or more deep learning frameworks, e.g., TensorFlow, Torch
• Extensive experience with OpenAI and Claude code-based prompt engineering; Hands-on experience developing and deploying AI Agents, RAG and vector/graph databases.
• Strong understanding of 3D geometry, vector math, and coordinate systems
• Proficiency in relevant 3D modeling or CAD software (e.g., Blender, Rivet) and/or programming libraries (e.g., OpenGL, CGAL, Three.js)

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Interested applicants can also email CV at harry@nsearchglobal.com (for faster processing, please state the exact job / position title applied “Data Scientist”

Only shortlisted candidates will be notified.

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EA License Number: 10C3636
EA Personnel Name: Arora, Hardeep
EA Personnel Registration Number: R1111454

By submitting your resume and cover letter to apply for our job opening, you confirm that you have read the Data Protection Notice for Job Applicants (https://www.nsearchglobal.com/dp-notice/job-applicants) and you consent to the collection, use, and disclosure of your personal data for the purpose of verifying and evaluating your job application. Additionally, you have to notify and obtain consent from all individuals listed as your references to their data being collected and disclosed for the purposes related to your job application

The intern will be attached to the Fleet Digital section and will support the team in the following activities: 

• Extract and analyze sets of data from multiple sources and database for Harbour Launch, Tugs and Crew Deployment; develop and test hypothesis and communicate with section managers recommendations. 

• Identify and interpret trends or patterns in the collected data sets. 

• Detect anomalies, spot discrepancies and possible defects from our Fleet Management System 

• Produce insights on operations data using analytic tools (Python/Excel/Power BI) 

• Design, develop and maintain ongoing reports and dashboards. 

• Take in the lead in digitalization projects by working with key stakeholders within and outside of organization. 

• Perform any other ad-hocs duties as assigned. 

Preferred Skills

• Proficiency in Python Programming Language and Excel VBA 

• Experience in UI/UX designing and able to develop dashboard with data visualization tools (Example: Power BI and Tableau) 

• Analytical mindset driven to understand machinery and operation data 

• Strong organizational and problem-solving skills 

• Commitment to learning including new analytical methods and Harbour Craft profile 

• Ability to identify data-driven insights and trends from large data sets, keeping in mind of data quality and accuracy 

• Able to develop Robotics Process Automation (RPA) – UiPath would be a plus. 

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

Role Overview:

We are looking for a Data Engineer to support large-scale government and defence-related data projects, focusing on building secure, scalable, and reliable data platforms and ETL/ELT pipelines across cloud and enterprise environments.

Job Responsibilities:

Data Engineering & Platform Development

• Design and develop scalable and reliable data pipelines.
• Build enterprise data platforms, including data warehouses, data lakes, and lakehouses.
• Implement cloud, hybrid, and on-premises data architectures aligned with enterprise standards.

ETL/ELT & Data Integration

• Lead ETL/ELT pipeline development, with Talend as a highly preferred platform.
• Integrate structured, semi-structured, and unstructured data sources.
• Implement and maintain data quality, validation, and error-handling frameworks.

Data Management & Governance

• Design and manage data storage solutions with a strong focus on object storage, data quality, and data governance.
• Implement and maintain data lifecycle management and cost-optimisation strategies.
• Ensure data lineage, traceability, and auditability.

Analytics & BI Enablement

• Engineer analytics-ready data models for reporting and self-service analytics.
• Enable BI dashboards, reports, and analytics through performant and governed data pipelines.

Security & Compliance

• Ensure compliance with government security and privacy requirements.
• Implement and maintain encryption, access controls, secure data handling practices, and system security policies.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum 3 years of experience in enterprise data engineering roles.
• Strong hands-on data engineering experience.
• Strong SQL and Python skills.
• Experience with ETL/ELT tools, with Talend highly preferred.
• Experience with data warehouses, data lakehouses, data lakes, and object storage systems.
• Qlik Sense Enterprise integration experience is highly preferred.
• Prior CAT 1 / G50 security clearance is required.
• Previous experience delivering MINDEF projects is required.

1. Position Summary

We are looking for a Data Engineer to join our team and contribute to a major project within the semiconductor manufacturing domain. The role involves designing and implementing data pipelines, managing Oracle-based data environments, and supporting end-to-end BI processes — from data ingestion to visualization. This position is based on-site at our partner’s advanced manufacturing facility, offering hands-on exposure to large-scale industrial data systems.

2. Key Responsibilities

• Design, develop, and maintain Python-based applications and APIs to extract, transform, and deliver data in JSON format.
• Design and create robust data models to support efficient querying and reporting.
• Define relationships, hierarchies, and calculated columns/measures that align with business logic.
• Design, develop, and maintain data pipelines and ETL workflows for manufacturing data (ERP, MES, SPC, FDC, etc.).
• Implement and optimize database logic, including stored procedures, functions, and PL/SQL scripts.
• Build and manage staging schemas, data validation processes, and data transformation logic.
• Develop and maintain data marts and dimensional models to support analytics and reporting.
• Collaborate with BI developers and analysts to deliver Power BI dashboards, KPI reports, and visual analytics.
• Ensure data accuracy, consistency, and completeness across multiple source systems.
• Support data governance, documentation, and performance tuning efforts.
• Partner with internal and external stakeholders to ensure timely and high-quality data delivery for business use.
• Perform any ad-hoc duties assigned by the Company as and when required.

3. Qualifications& Skills

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Minimum 3 years of experience in data engineering, data integration, or BI development.
• Proficient in Python programming, specifically for data extraction, API development, and JSON data manipulation.
• Strong understanding of data warehousing concepts, schema design, and ETL best practices.
• Solid working experience with relational databases (e.g. Oracle, SQL Server, MySQL, PostgreSQL), including stored procedures and query optimization.
• Proficient with ETL tools such as Pentaho Kettle, Informatica, Talend, or similar.
• Experience developing reports and dashboards in Power BI (or Tableau/Qlik).
• Familiarity with SQL pipelines, data validation, and data replication tools.
• Strong analytical and problem-solving mindset with attention to data quality and performance.
• Ability to work collaboratively with business, IT, and engineering teams in fast-paced environments.
• Excellent documentation and communication skills.

4. Preferred /Additional

• Experience in semiconductor or manufacturing systems (ERP, MES, SPC, FDC) preferred.
• Exposure to data replication frameworks (Oracle Golden Gate, SharePlex, AWS Glue) is an advantage.
• Experience developing custom Python applications/APIs for data extraction and familiarity with JSON data structures is highly preferred.
• Familiarity with cloud-based data warehouses (Snowflake, Redshift, Synapse) and Giga Report is a plus
• Knowledge of data governance frameworks, metadata management, and data security best practices.

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Responsibilities

We are looking for a seasoned BAU Lead - Data Engineering to lead our data

operations and support function in a cloud-first environment. The ideal

candidate will bring strong technical leadership, hands-on expertise in AWS

and Snowflake, and proven experience in managing Business-As-Usual (BAU)

data platforms, production support, and continuous improvement initiatives.

▪ Develop tools to improve data flows between internal/external systems

and the data lake/warehouse.

▪ Work with stakeholders to understand needs for data structure, availability,

scalability, and accessibility.

▪ Build robust and reproducible data ingest pipelines to collect, clean,

harmonize, merge, and consolidate data sources.

▪ Understanding existing data applications and infrastructure architecture

▪ Build and support new data feeds for various Data Management layers and

Data Lakes

▪ Evaluate business needs and requirements.

▪ Support migration of existing data transformation jobs in Oracle, and MS[1]SQL to Snowflake.

▪ Lead the migration of the existing data transformation jobs in Oracle, Hive,

Impala etc. into Spark, Python on Glue etc.

▪ Able to document the processes and steps.

▪ Develop and maintain datasets.

▪ Improve data quality and efficiency.

▪ Lead Business requirements and deliver accordingly.

▪ Collaborate with Data Scientists, Architect and Team on several Data

Analytics projects.

▪ Collaborate with DevOps Engineer to improve system deployment and

monitoring process.

▪ Experience in critical production support and how the BAU functions is

preferred.

Requirements Key Skills:

▪ Lead a team of data engineers in managing day-to-day BAU operations,

production support, incident management, and platform stability.

▪ Strong AWS knowledge in terms of designing new architecture and

providing optimized solutions for existing ones. (S3, Glue, DMS, MWAA,

AMS, IAM).

▪ In-depth knowledge with respect to Snowflake and its architecture.

▪ Prefer prior Experience in BAU environment.

▪ Good knowledge on Airflow and MWAA.

▪ Hands-on experience in SQL/Python/Pyspark.

▪ Expertise in optimizing techniques in cloud environments.

▪ Should have the vision on data strategy and able to deliver the same.

▪ Should be able to lead the design and implementation of data management

processes, including data sourcing, integration, and transformation.

▪ Able to manage and lead a team of data professionals, providing guidance,

mentoring and foster a collaborative and innovative team culture focused on

continuous improvement.

▪ To evaluate and recommend data-related technologies, tools, and

platforms.

▪ Collaborate with IT teams to ensure seamless integration of data solutions.

▪ Should have experience in Implementing and enforcing data security

protocols and ensure compliance with relevant regulations.

Required Qualifications:

▪ At least 8+ years of Data Engineer Experience

▪ Bachelor qualification in a computer science or STEM (science, technology,

engineering, or mathematics) related field.

▪ At least 5+ years of recent hands-on professional experience (actively

coding) working as a Lead handling support & production issue.

▪ 2+ experience with large scale datasets, data lake and data warehouse

technologies such as AWS Redshift, Google BigQuery, Snowflake. Snowflake

is highly preferred.

▪ At least 3+ years of experience in ETL (AWS Glue), Amazon S3, Amazon

RDS, Amazon Kinesis, Amazon Lambda, Apache Airflows, Amazon Step

Functions.

▪ Professional experience working in an agile, dynamic and customer-facing

environment is required.

▪ Understanding of distributed systems and cloud technologies (AWS) is

highly preferred.

▪ Understanding of data streaming and scalable data processing is preferred

to have.

▪ Strong knowledge in scripting languages like SQL ,Python, UNIX shell and

Spark is required.

▪ Understanding of RDBMS, Data ingestions, Data flows, Data Integrations

etc.

▪ Technical expertise with data models, data mining and segmentation

techniques.

▪ Experience with full SDLC lifecycle and Lean or Agile development

methodologies.

▪ Knowledge of CI/CD and GIT Deployments.

▪ Ability to work in team in diverse/ multiple stakeholder environment.

▪ Ability to communicate complex technology solutions to diverse teams

namely, technical, business and management teams

Soft Skills

▪ Ability to work in a collaborative environment and coach other team

members on coding practices, design principles, and implementation

patterns that lead to high quality maintainable solutions.

▪ Excellent communications and stake-holder management are required.

▪ Ability to handle senior leadership and report to them if required.

▪ Ability to work in a dynamic, agile environment within a geographically

distributed team.

▪ Ability to focus on promptly addressing customer needs.

▪ Ability to work within a diverse and inclusive team.

▪ Technically curious, self-motivated, versatile and solution-oriented

Responsibilities:

• Data Infrastructure: Build, implement, and maintain scalable data pipelines and storage architectures.
• Data Quality: Maintain strong data integrity by ensuring reliability, consistency, and accuracy across all data processes.
• Performance Optimization: Enhance system efficiency by tuning data processing workflows and improving large-scale performance.
• Process Improvement & Mentoring: Strengthen data engineering practices while providing guidance and support to junior engineers.
• Cross-Functional Collaboration: Partner with business analysts, data scientists, and backend teams to deliver timely and actionable data solutions.

Qualifications:

• 5+ years’ experience in data engineering or backend roles, with strong programming skills in Python or Java/Scala.
• Hands-on experience with big data tools: Spark, Flink, Kafka, Airflow, and cloud platforms (AWS, GCP, Azure); proficient in SQL.
• Skilled in designing and maintaining data models, warehouses, and ETL/ELT pipelines for scalable, reliable systems.
• Knowledgeable in data quality, governance, security, and compliance best practices.

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

Wecruit Pte Ltd
EA License No: 20C0270
EA Personnel: Nyon Hock Sen (Aden)
EA Personnel Reg No: R24124070

We are looking for an ambitious Marketing Executive to help us increase our clients‘ Brand awareness and Customer base through the promotion of their products and services at our event sites in Singapore.

As a member of our Marketing team, you will have room to advance your career. Our employees receive 1-on-1 coaching/mentorship, continuous training and assistance, travel opportunities, leadership opportunities to coach newcomers and fast tracked career progression/growth.

Responsibilities

- Participate and ensure the successful execution of our events marketing campaigns

- Promote our products or services to existing and potential customers

- Work with the rest of the Marketing team to develop promotion strategies and oversee their implementation

Requirements

- Background in Sales, Marketing, or similar roles is a plus

- Open minded and willingness to learn

- Good communication and presentation skills is a plus

We are looking for an ambitious Marketing Executive to help increase our clients’ brand awareness and customer base through the promotion of products and services at our event sites across Singapore.

As part of our marketing team, you’ll gain hands-on experience in live campaigns and brand activations, while working in a structured environment focused on learning, performance, and growth. You will also be exposed to team development and recruitment processes, with opportunities to progress into leadership roles where you may guide and lead campaigns independently over time.

Employees receive structured 1-on-1 coaching, continuous training, and ongoing support, alongside opportunities for regional travel, leadership development, and fast-tracked career progression based on performance.