Total 863 data entry job vacancies in Information Technology category in Hong Kong

• 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

Join Our Team – Data Admin
We are seeking a detail-oriented and organised individual to support data cleaning and reconciliation work. You will be responsible for updating records, verifying information, resolving discrepancies, and ensuring data accuracy across systems.

Job Summary

Support digitalisation initiatives by developing dashboards to improve visibility of operational risks and hazards. This role focuses on creating user-friendly data visualisation tools to enhance workplace safety and decision-making.

Job Responsibilities

• Design and develop dashboards to visualise risks and hazards across operational areas
• Gather and organise data to ensure accuracy and clarity in reporting
• Work with stakeholders to understand requirements and improve dashboard usability
• Maintain and update dashboards to reflect latest data and insights
• Support digitalisation and process improvement initiatives

Requirements

• Diploma in a relevant field (e.g. Engineering, IT, Data Analytics)
• Knowledge of dashboard tools such as Power BI, Power Apps, or similar platforms

All qualified applicants, please click “ APPLY NOW”

Or you may send in your resume to:

Whatsapp: https://wa.me/+6597430026  

Email : kimlow@recruitexpress.com.sg

Kimmy Low Yi Ting (Kim) | CEI Registration Number: R23112122

Recruit Express Pte Ltd Company Reg. No. 199601303W | EA LICENCE Number: 99C4599

Good understanding of CPG DomainHands on Experience on Nielsen Data setsGood command on MS Excel and Powerpoint

As a key team member, You would be responsible for collecting, transforming and validating the data required for MMM Models.

Using Advanced Excel & Python, you would be required to manipulate and transform the raw data into model ready datsets.  The processed data needs to be warehoused in Azure and presented using PowerBI.  You would have to validate and derive insights from the transformed data to assist modeling team in building hypotheses for the MMM Models.  This will be for various datasets – Consumption or POS data, Media – both online and offline, Medical Expert & Finance data

You will be seen as a strong voice of influence for sharing ideas and contributing to innovation of the entire data ingestion process from source to modeling

Work Experience

2-8 years of experience in Data Analytics, Data Manipulation, Modeling in CPG or Consumer Pharma Domain.

Qualification

• M.Sc. Statistics
• M.Sc. Operational Research
• M.Sc. Mathematics
• B. Sc. Stats + MBA
• B. Tech.

Role Requirements:

• Robust knowledge on Consumer Industry Brands & Category, knowledge on CPG data processing (with sales / marketing / commercial operations teams). Able to source data from external syndicated data provider’s portals.
• Knowledge of Marketing Mix Modeling, Pricing, RGM or any other Advanced analytics solution for CPG and Pharma domain
• Experience of working on Nielsen, IRI, IQVIA datasets
• Experience of working on Media data – offline or online for CPG or Pharma clients
• Manipulating data using Advanced excel, Python or R; Knowledge of any BI tools – PowerBI preferred; Knowledge of Azure platform is a plus
• Identifying new ways to leverage data (internal and external data sets -  sales, digital, advertisement, media, sales force, social) to generate business insights
• Demonstrate technical functional expertise and be seen as an expert and partner by the client and internal stakeholders
• Fluent verbal communication and good written communication, communicate statistical outputs in a business language
• Run small to medium size projects, and manage the execution by planning project activities, tracking and monitoring the tasks, and working with close coordination with the project manager
• Provide training and support for internal employees
• Well-developed conceptual, analytical, strategic thinking and problem solving skills. High sense of ownership
• Proven ability to handle multiple projects while meeting deadlines and documenting progress towards those deadlines
• Provide support to global markets and display flexibility
• Nice to have
  • Machine Learning (ML), DevOps, Azure Data bricks experience/understanding
  • Preferred knowledge/experience in R, SQL and PL/SQL, Power BI, Azure

Shift Time: 8:00 AM to 5:00 PM IST

Description
A manufacturing company in Singapore is hiring a full-time Technical Service Technician. You will support production by operating equipment, performing preventive maintenance, and troubleshooting to meet output and quality targets. Training will be provided, fresh graduates are welcome.

Key Responsibilities
• Operate manufacturing equipment to meet production schedule and output targets
• Troubleshoot equipment issues to minimise downtime and meet quality standards
• Perform daily and monthly preventive maintenance to improve equipment reliability
• Support workplace safety practices and participate in quality improvement projects
• Maintain basic records for maintenance activities and equipment performance

Requirements
• Minimum NITEC in an Engineering discipline (Mechanical, Mechatronics, Robotics, or related)
• Able to read and understand electrical and mechanical diagrams
• Comfortable with 12-hour shift work and willing to work overtime when required
• Able to lift and carry 10–15kg
• Willing to work in a controlled manufacturing environment
• Open to fresh graduates

Shift Pattern
• 12-hour shift, 4-3-3-4 work/rest cycle
Week 1: Work 4 days, rest 3 days
Week 2: Work 3 days, rest 4 days
Repeat cycle
• Assigned shift: Sunday Night Shift, 7:45pm to 7:55am

Salary & Allowances
• Basic Salary: Up to $2,100 per Month
• Allowances: Up to $400++ per Month

Location
• Jurong East

Interested?
Kindly WhatsApp 8839 0096 and mention “Technical Service Technician”.

Only shortlisted candidates will be notified.

Epiphanius Tan (R26160523)
Crew By HRnet | HRnet Ventures Pte Ltd
EA24C2435

About the Role

As the Head of AI Engineering, you will lead and scale our AI Engineering function across enterprise deployments. You will define the technical vision, build and mentor a high-performing team, and ensure that AI solutions move beyond proof-of-concept into reliable, production-grade systems that drive measurable business impact.

This is a player-coach role — you will both guide strategy and remain close to the technology. You will oversee multiple enterprise engagements, shape system architecture standards, and ensure delivery excellence across all implementations.

You will own the success of AI delivery at scale — from technical direction and team capability to customer outcomes.

What You'll Do

AI Engineering Leadership

• Define and drive the overall AI engineering strategy, architecture standards, and best practices
• Build, mentor, and lead a team of AI engineers across multiple projects
• Establish scalable delivery processes, code standards, and quality benchmarks
• Create a strong engineering culture focused on ownership, speed, and impact

Enterprise AI Delivery Oversight

• Oversee end-to-end delivery of AI solutions across enterprise clients
• Ensure teams deliver from discovery → design → deployment → adoption successfully
• Act as escalation point for complex technical or delivery challenges
• Work closely with customers and stakeholders to ensure solutions align with real business needs

Agentic AI & System Architecture

• Define architecture patterns for multi-agent systems, orchestration, and AI workflows
• Guide teams in building reliable, production-ready agentic systems (LangChain, LangGraph, etc.)
• Ensure best practices in:
• LLM orchestration
• RAG pipelines
• evaluation & monitoring
• human-in-the-loop design

Technical Strategy & Innovation

• Stay at the forefront of AI advancements (LLMs, agents, infra) and translate them into practical use cases
• Evaluate tools, frameworks, and infrastructure to standardize across teams
• Drive internal innovation — reusable frameworks, templates, and tooling

Product & Cross-functional Impact

• Identify patterns across enterprise projects and translate them into product opportunities
• Partner with Product and Engineering leaders to influence roadmap
• Drive development of internal platforms, reusable assets, and accelerators

Operational Excellence

• Define KPIs for delivery success (adoption, performance, ROI)
• Ensure systems are scalable, observable, and maintainable
• Improve delivery speed through reusable components and standardized workflows

Must-Haves

• 5+ years in software engineering, with 3–5+ years in AI/ML systems in production
• Proven experience leading engineering teams or technical organizations
• Deep hands-on experience with:
• LLMs (OpenAI, Anthropic, Gemini, OSS models)
• Prompt engineering, RAG, fine-tuning, evaluation
• Agentic AI systems (multi-step reasoning, tools, memory)
• Strong system design skills across APIs, cloud (AWS/GCP/Azure), and data systems
• Experience working with enterprise clients or complex environments
• Strong ownership mindset — accountable for outcomes, not just delivery

• Hybrid work
• Health insurance
• Annual health check
• Laptop and other equipments
• Free snacks & drinks
• Weekly massage
• Grab transportation credit
• Education allowance
• Performance bonus

• Generate data-driven hypotheses to solve key Product/Business problems

• Use data to identify trends, spot anomalies and deep dive into their root causes

• Partner closely with the broader product and engineering team to design and analyze experiments that drive key product decisions, deep dive into existing data to recommend new product ideas to solve for the most impactful customer problems

• Design and own frontend and backend data specs for new products, while collaborating with engineering teams to ensure accurate and timely data collection, consolidate data from multiple sources to create integrated and scalable views that can be used to drive decision making

• Provide catered analysis for specific products and operations, define critical business metrics and track them rigorously, and provide regular recommendations to achieve continuous improvements

• Work closely with stakeholders to understand their needs/ pain points to scope up their problems and enhance internal processes through automation and improve productivity

Job Responsibilities:

• Analyse, correlate, interpret and visualise data to uncover trends and patterns.
• Formulate and test threat hunting hypothesis.
• Produce insights and supporting evidence to support decision making.
• Compile and share intel with counterparts for prompt intervention actions.
• Translate concepts and results into reports and presentation for senior stakeholders

Job Requirements:

• Degree in Computer Science / Computer Engineering / Mathematics / Statistics / Data Science and Analytics or equivalent.
• Knowledge of cybersecurity concepts and applications. Candidates with relevant cybersecurity certifications are preferred.
• At least 5 year of experience in data transformation, interpretation, and quantitative data analysis.
• Knowledge of statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with their application is preferred.
• Experience in using databases and frameworks for big data analytics such as Hadoop / Hive / Spark, and able to write complex SQL queries.
• Domain knowledge and experience in Computer Networking, Network Security, or System Security is preferred.
• Good writing, communication and presentation skills.
• Fast learner with self-motivation and independence to acquire knowledge on new domains or technologies quickly.

To Apply, please kindly email your updated resume to weizhe.teoh@tg-hr.com

Regret to inform that only shortlisted candidates will be notified.

CEI: R25127749

EA License: 14C7275

Job Overview

We are seeking a skilled and motivated Data/AI Compliance Analyst to join our team. This is a dual-role position that combines data analysis, AI compliance coordination, and AI audit support.

The role will support both data-driven business improvement and the governance, tracking, and follow-up of AI compliance and audit-related actions across internal products and initiatives. The successful candidate will work closely with cross-functional teams to analyse data, improve reporting and operational visibility, and help ensure that AI-related systems, processes, and use cases are properly documented, monitored, and aligned with internal governance, compliance, and audit requirements.

As a Data/AI Compliance Analyst, you will bridge the gap between data, operations, business processes, and AI governance, helping the organisation turn information into actionable insight while strengthening accountability, control, and follow-through on AI risk and compliance matters.

Key Responsibilities

A. Data Analyst Responsibilities

• Analyse business processes and identify opportunities for optimisation through data-driven insights and reporting.

• Collaborate with stakeholders to define key performance indicators (KPIs), business goals, and reporting requirements.

• Conduct data analysis to derive actionable insights that support business decisions, operational improvements, and management reporting.

• Identify, analyse, and interpret trends or patterns in data sets related to business performance, operational issues, system performance, and user behaviour.

• Clean, transform, validate, and maintain data to ensure accuracy and consistency across reporting and analysis.

• Design and maintain dashboards, reports, and visualisations using BI tools such as Power BI and Tableau.

• Support exploratory data analysis to uncover insights and improve understanding of business and system performance.

• Work with product, development, and business teams to improve reporting structures, data visibility, and analytics processes.

• Prepare clear presentations, reports, and summaries of findings for technical and non-technical stakeholders.

• Participate in system and process improvement discussions to ensure alignment between analytics needs and business objectives.

B. Compliance Analyst Responsibilities

• Support the development and maintenance of registers, logs, and documentation related to AI use cases, risks, incidents, controls, and action items.

• Track and follow up on AI compliance, audit, and governance action items, ensuring owners are identified, timelines are monitored, and findings are closed in a timely manner.

• Support internal reviews, governance checks, and audit preparation for AI-related initiatives, including gathering evidence and maintaining organised supporting documentation and audit trails.

• Assist in monitoring adherence to AI governance frameworks, internal policies, and relevant standards or control requirements.

• Work with product, development, and business teams to ensure that AI solutions are supported by required documentation, testing records, issue tracking, and control evidence.

• Help identify compliance gaps, process weaknesses, and control improvement opportunities related to AI systems, workflows, and data handling practices.

• Support the preparation of compliance updates, audit status reports, management summaries, and governance materials.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Analytics, Statistics, or a related discipline.

• Proven experience in data analysis, reporting, business systems analysis, or business intelligence.

• Strong understanding of business processes, reporting structures, and how data supports decision-making.

• Proficiency in tools such as Excel, SQL, Power BI, Tableau, Python, or similar analytics and reporting platforms.

• Experience in data wrangling, dashboard development, visualisation, and reporting.

• Strong analytical and problem-solving skills with attention to detail.

• Good written and verbal communication skills, with the ability to present findings clearly to both technical and non-technical stakeholders, and to prepare compliance updates, summaries, and status reports.

• Experience in maintaining trackers, registers, logs, action lists, and documentation for compliance or audit purposes.

• Strong organisational skills with the ability to manage multiple follow-ups, monitor action items, and ensure closure.

• Ability to work across teams to coordinate updates, gather evidence, and support governance and audit requirements.

• Proactive, disciplined, and able to drive accountability and follow-through across stakeholders.

• Exposure to AI compliance, AI governance, AI risk management, or AI audit practices will be an advantage.

• Experience in compliance tracking, audit coordination, governance support, risk tracking, or control documentation will be an advantage.

Job Overview

We are seeking a skilled and motivated Data/AI Compliance Analyst to join our team. This is a dual-role position that combines data analysis, AI compliance coordination, and AI audit support.

The role will support both data-driven business improvement and the governance, tracking, and follow-up of AI compliance and audit-related actions across internal products and initiatives. The successful candidate will work closely with cross-functional teams to analyse data, improve reporting and operational visibility, and help ensure that AI-related systems, processes, and use cases are properly documented, monitored, and aligned with internal governance, compliance, and audit requirements.

As a Data/AI Compliance Analyst, you will bridge the gap between data, operations, business processes, and AI governance, helping the organisation turn information into actionable insight while strengthening accountability, control, and follow-through on AI risk and compliance matters.

Key Responsibilities

A. Data Analyst Responsibilities

• Analyse business processes and identify opportunities for optimisation through data-driven insights and reporting.

• Collaborate with stakeholders to define key performance indicators (KPIs), business goals, and reporting requirements.

• Conduct data analysis to derive actionable insights that support business decisions, operational improvements, and management reporting.

• Identify, analyse, and interpret trends or patterns in data sets related to business performance, operational issues, system performance, and user behaviour.

• Clean, transform, validate, and maintain data to ensure accuracy and consistency across reporting and analysis.

• Design and maintain dashboards, reports, and visualisations using BI tools such as Power BI and Tableau.

• Support exploratory data analysis to uncover insights and improve understanding of business and system performance.

• Work with product, development, and business teams to improve reporting structures, data visibility, and analytics processes.

• Prepare clear presentations, reports, and summaries of findings for technical and non-technical stakeholders.

• Participate in system and process improvement discussions to ensure alignment between analytics needs and business objectives.

B. Compliance Analyst Responsibilities

• Support the development and maintenance of registers, logs, and documentation related to AI use cases, risks, incidents, controls, and action items.

• Track and follow up on AI compliance, audit, and governance action items, ensuring owners are identified, timelines are monitored, and findings are closed in a timely manner.

• Support internal reviews, governance checks, and audit preparation for AI-related initiatives, including gathering evidence and maintaining organised supporting documentation and audit trails.

• Assist in monitoring adherence to AI governance frameworks, internal policies, and relevant standards or control requirements.

• Work with product, development, and business teams to ensure that AI solutions are supported by required documentation, testing records, issue tracking, and control evidence.

• Help identify compliance gaps, process weaknesses, and control improvement opportunities related to AI systems, workflows, and data handling practices.

• Support the preparation of compliance updates, audit status reports, management summaries, and governance materials.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Analytics, Statistics, or a related discipline.

• Proven experience in data analysis, reporting, business systems analysis, or business intelligence.

• Strong understanding of business processes, reporting structures, and how data supports decision-making.

• Proficiency in tools such as Excel, SQL, Power BI, Tableau, Python, or similar analytics and reporting platforms.

• Experience in data wrangling, dashboard development, visualisation, and reporting.

• Strong analytical and problem-solving skills with attention to detail.

• Good written and verbal communication skills, with the ability to present findings clearly to both technical and non-technical stakeholders, and to prepare compliance updates, summaries, and status reports.

• Experience in maintaining trackers, registers, logs, action lists, and documentation for compliance or audit purposes.

• Strong organisational skills with the ability to manage multiple follow-ups, monitor action items, and ensure closure.

• Ability to work across teams to coordinate updates, gather evidence, and support governance and audit requirements.

• Proactive, disciplined, and able to drive accountability and follow-through across stakeholders.

• Exposure to AI compliance, AI governance, AI risk management, or AI audit practices will be an advantage.

• Experience in compliance tracking, audit coordination, governance support, risk tracking, or control documentation will be an advantage.

Required Skills & Qualifications

• Bachelor’s or master’s degree in operations research, Computer Science, Data Science, or a related quantitative discipline, with a strong foundation in optimization, simulation, and algorithmic problem‑solving.
• Minimum of 3 years of hands‑on experience in 3D modelling and simulation using platforms such as NVIDIA Omniverse or equivalent tools.
• Strong proficiency in Python, R, SQL, and modern data engineering practices.
• Practical experience with machine learning frameworks such as TensorFlow and PyTorch, as well as simulation and modeling tools.
• Solid understanding of semiconductor manufacturing processes and fab operations.
• Familiarity with IoT data pipelines, MES systems, and cloud platforms such as AWS and Azure.

Key Responsibilities

• Collaborate with a global, cross‑functional team of data scientists, data engineers, solution architects, external partners, and stakeholders from construction, facilities, and planning teams to develop highly accurate digital twins of semiconductor fabs.
• Enable advanced digital twin capabilities, including photorealistic visualization and physics‑based simulation, to support planning and operational decision‑making.
• Design, build, and maintain data‑driven models that represent semiconductor fab processes,equipment behavior, and sub‑fab utility systems.
• Integrate IoT sensor data, Manufacturing Execution System (MES) data, and facility data into the digital twin platform to ensure real‑time and historical insight.
• Develop predictive analytics and machine learning models for predictive maintenance, throughput optimization, energy efficiency, and yield improvement.
• Apply statistical and ML techniques to forecast equipment failures, cycle time variability, and potential yield impacts.
• Leverage simulation tools such as NVIDIA Omniverse to conduct what‑if analysis for layout planning, capacity expansion, and process optimization.
• Optimize fab workflows to improve cost efficiency, energy consumption, and overall productivity.
• Design and deliver dashboards for real‑time monitoring of key fab KPIs, including OEE, WIP, and energy usage.
• Partner with engineering teams to visualize fab layouts, system states, and operational scenarios within immersive 3D environments.
• Support and contribute to cross‑functional initiatives related to AI, automation, Industry 4.0, and smart manufacturing solutions.

To Apply:

Interested applicants please send your resume in MS Words format to pooja.yadav@ambition.com.sg and attention to Pooja (R1551322)

Short listed candidates will be notified

www.ambition.com.sg

EA Registration Number: R1551322

Data provided is for recruitment purposes only

Business Registration Number: 200611680D.

License Number: 10C5117

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

Situated in the heart of Singapore's Central Business District, Rakuten Asia Pte. Ltd. is Rakuten's Asia Regional headquarters. Established in August 2012 as part of Rakuten's global expansion strategy, Rakuten Asia comprises various businesses that provide essential value-added services to Rakuten's global ecosystem. Through advertisement product development, product strategy, and data management, among others, Rakuten Asia is strengthening Rakuten Group's core competencies to take the lead in an increasingly digitalized world.

Department Overview

The Data Lake house Section provides the foundation for Rakuten Digital Twin strategy enabling seamless, real-time understanding of customers across services. 
We manage one of the world's largest first-party datasets, developing and operating products like Customer DNA (CDNA) and Deep CDNA, which unify data across business units. 

As a Senior Data Engineer, you will play a key role in the architecture, development, and optimization of Rakuten's core data platform. 
You will lead engineering efforts to design scalable, reliable, and secure data pipelines and collaborate closely with global teams in Japan and India.

Responsibilities:

- Lead the design, development, and operation of scalable and reliable data pipelines supporting Customer DNA and related data products.
   
- Drive best practices in data engineering, including performance tuning, automation, and observability.
   
- Collaborate with product managers, data scientists, and analytics engineers to deliver end-to-end solutions.
   
- Oversee data ingestion, transformation, and quality control processes to ensure trusted data availability.
   
- Design and optimize data architectures leveraging Google Cloud Platform(GCP) services (e.g., Big Query, Dataflow, Pub/Sub, Cloud Storage).
   
- Mentor team members, promote engineering excellence, and contribute to a culture of learning and collaboration.
   
- Ensure compliance with data governance, security, and privacy standards across systems.
   
Qualifications:

- 5+ years of experience building and operating big data platforms for analytics or business operations.
   
- 2+ years of experience managing large-scale, real-time or unstructured datasystems in distributed environments.
   
- Proficiency in Python programming and related libraries (e.g., Pandas, NumPy, PySpark, Pydantic).
   
- Strong hands-on experience with Google Cloud Platform (GCP), including Big Query, Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, and IAM.
   
- Experience with Infrastructure-as-Code (IaC), CI/CD pipelines, and cloud resource management.
   
- Experience with **containerization (Docker)** and **orchestration (Kubernetes)** in cloud-native environments.
   
- Strong understanding of **SQL and NoSQL** data stores, with experience inlarge-scale distributed systems.
   
- Proven ability to identify and solve complex data engineering challenges, ensuring system reliability and scalability.
   
- Excellent communication and leadership skills, with experience guidingcross-functional or remote teams.
   
- Business-level proficiency in English.

- Proficiency in Japanese will be an advantage, as the role involves communication with Japanese-speaking stakeholders.

Good to have:

- Experience designing Python-based data engineering frameworks ensuring scalability, performance, and maintainability.
   
- Experience developing and maintaining reusable Python packages and libraries for data pipelines.
   
- Familiarity with API-based data integration and micro service architectures.
   
- Experience implementing cloud-native data solutions to optimize cost and performance.
   
- Proven ability to balance hands-on technical contribution with strategic leadership.
   
- Ability to mentor engineers and promote best practices in software craftsmanship.
   
Rakuten is an equal opportunities employer and welcomes applications regardless of sex, marital status, ethnic origin, sexual orientation, religious belief, or age.
   

Experience: 6+ years experience in large dataplatform and large‑scale datamigration in Cloudera ADF & Databricks

KeyResponsibilities (R&R)

• Own end‑to‑end historical data migration from Cloudera (Hive/HDFS) and legacy systems
• Design and execute one‑off bulk history migration
• Design daily incremental loads via ADF, fully metadata‑driven
• Implement migration using customer ingestion framework or custom framework
• Design restartable, idempotent migration pipelines
• Build reconciliation reports (counts, checksums, balances)
• Develop automated testing packs for HDM (history data migration)
• Handle schema drift, data quality issues, and legacy anomalies
• Support parallel run, cutover, and business sign‑off
• Act as migration SPOC across platform, ingestion, and business teams

MandatorySkills (Must‑Have)

• Azure Data Factory (ADF) – metadata‑driven pipelines
• Basic Cloudera working knowledge
• Cloudera → Cloud migration (mandatory)
• Large‑volume historical data migration
• Azure Databricks (Spark / SQL)
• Data reconciliation and audit sign‑off
• Framework‑based data ingestion / migration

Good‑to‑Have

• Azure Data Box–based migration experience
• Bulk history extraction using Data Box
• Landing data into ADLS Gen2
• Processing history in Databricks (Delta)
• Orchestrating incrementals via ADF

The Data Center Facilities Engineer is a primarily administrative and coordination‑focused role supporting both local and data center operations. This position acts as an on‑site coordination point between operations stakeholders, facilities teams and network resolver teams, to ensure activities are executed smoothly, accurately tracked, and fully documented during live operations.

While the role is not a primary break‑fix position, it requires both basic DC operations and networking knowledge to support coordination, validation, and observation of general DC and network‑related activities. Hands‑on interaction with network equipment is expected at a foundational level.

Key Responsibilities:

Operations Coordination & Administration

• Coordinate with network, facilities, and other resolver teams during incidents, maintenance, and change activities.
• Track and monitor operational activities to ensure tasks are executed according to approved procedures.
• Maintain accurate and timely operational records, including:
• Incident and service request logs, Change and maintenance records, Shift handover documentation, Escalation and resolution updates
• Provide clear status updates and facilitate escalations during ongoing operations.
• Respond and deal with emergency events in daily operation.

Facilities & Environment Monitoring

• Monitor data center facilities systems including power, cooling, temperature, humidity, and alarms via the Building Management System (BMS).
• Acknowledge, log, and coordinate responses to routine facilities and environmental alerts.
• Support emergency events by coordinating response teams, documenting actions, and ensuring follow‑up activities are completed.

Network Resident Technician Support

• Provide basic network support assistance such as:
• Visual inspection of network equipment and indicators, Verifying port labels, cabling connections, and link status, Supporting guided reboots or checks under instruction from resolver teams
• Act as an on‑site liaison for remote network engineers, ensuring work is correctly executed and documented.
• Support rack‑and‑stack activities for network equipment under approved procedures.

On‑Site Access & Compliance

• Escort and supervise vendors, visitors, and technicians working within the data center.
• Witness and document work performed on facilities and network equipment.
• Ensure compliance with safety standards, regulatory requirements, and company policies.
• Support physical security processes including access control, key management, and visitor logging.

Record Keeping & Asset Management

• Maintain and update operational, maintenance, inventory, and asset records.
• Support inventory tracking for facilities and network equipment (e.g., DCIM or asset tools).
• Ensure documentation accuracy to support audits and operational reviews.

Other Bank Compliance

• Ensure adherence to bank compliance that will be provided as part of the training.

 Required Qualifications

• Minimum 1 year experience in data center operations, facilities support, or resident technician roles.
• Diploma or Degree in Electrical Engineering, Mechanical Engineering, IT, Computer Science, Networking, or a related field.
• Strong administrative and coordination skills, with experience managing tickets, records, and operational documentation.
• Basic networking knowledge, including:
• Understanding of network devices (switches, routers, firewalls), Structured cabling concepts and patching, Rack layouts and port identification
• Familiarity with data center environments, including power, cooling, fire protection, temperature, and humidity control.
• Proficient in Microsoft Office (Excel, Word, PowerPoint).
• Good command of English for operational communication and documentation.
• Willingness to work rotating shifts, including weekends and public holidays.

Good‑to‑Have / Advantageous Skills

• Hands‑on experience with network equipment installation, replacement, or troubleshooting.
• Experience with rack & stack for network devices.
• Exposure to structured cabling standards and labeling practices.
• Experience with DCIM or inventory tools (e.g., Nlyte).
• Familiarity with physical security operations in a data center environment.
• Local language proficiency is an advantage.

 Working Environment:

• There are 3 Shifts:

• Morning shift (M-F): 7:00AM to 4:00PM, Afternoon shift (M-F): 12:00NN to 9:00PM, Weekend Shift (Sat & Sun): 9:00AM to 6:00PM

  (Overtime is compensated)