Total 773 data entry job vacancies

This is a full-time role for a Data Engineer. The Data Engineer will be responsible for designing and implementing scalable data pipelines, developing and maintaining data models, performing Extract, Transform, Load (ETL/ELT) processes, and managing modern data warehousing and analytics solutions—primarily utilizing Microsoft Fabric and Databricks. The role also includes building and operationalizing lakehouse architectures, ensuring data governance and security best practices, and analyzing complex datasets to support business decision-making. Collaboration with cross-functional teams to deliver high-quality data solutions is essential. 

Qualifications 

• Strong proficiency in Data Engineering, Data Modelling, and building Lakehouse/Data Warehouse solutions 

• Demonstrates strong proficiency in Medallion architecture and metadata-driven concepts. 

• Hands-on experience with Microsoft Fabric (Data Factory, Lakehouse, Warehouse, OneLake, Data Activator, Power BI integration) 

• Hands-on with Databricks (Spark, Delta Lake, DLT pipelines, Unity Catalog) 

• Proficiency in ETL/ELT development and orchestration within Azure ecosystem 

• Strong skills in Data Analytics using SQL, Python or PySpark 

• Knowledge of Cloud-native data platforms including Azure Data Lake, Azure Synapse, Azure Data Factory, Azure Storage, etc. 

• Understanding of data governance, security, and CI/CD best practices for cloud data platforms 

• Strong problem-solving and analytical skills 

• Ability to work independently and remotely in a fast-paced environment 

• Bachelor’s degree in computer science, Information Technology, or related field 

Company Overview

TECHCOM SOLUTIONS, founded in 2003, is a Singapore-based IT total solutions provider serving government agencies, MNCs, system integrators, educational institutions, and BFSI across Singapore and APAC. We specialize in outsourcing, managed services, and staffing solutions.

Job Summary

You will develop and optimize data integration pipelines and ETL/ELT codes using Teradata SQL, Informatica, and Apache Spark to support data warehousing and analytics. You will also automate workflows and enhance application performance to drive efficient data operations.

Responsibilities

• Develop ETL/ELT codes using Teradata SQL, Informatica PowerCenter, Apache Spark, QueryGrid, and Trino to transform and load data into Teradata data warehouses and datamarts
• Optimize and tune performance of complex data applications to reduce resource consumption and improve efficiency
• Design and implement data pipeline orchestration frameworks using GCFR, shell scripting, and BTEQ to automate end-to-end data workflows
• Integrate automation frameworks with control systems to ensure reliable and scalable data processing
• Apply CDC (Change Data Capture) concepts, preferably with Java-based implementations, to support real-time data updates
• Utilize Apache Spark and Hadoop ecosystem tools (Hive, Kafka, NiFi, Iceberg, Impala) to manage and process large-scale data sets
• Write and maintain shell scripts and BTEQ scripts to support data operations and automation tasks

Preferred competencies and qualifications

• 6+ years of relevant experience in data engineering and ETL development

Job Description:

Combine AI/ML and Technology knowledge to implement highly scalable solutions to solve real-world problems in areas such as Generative AI, Personalization, Image Recognition, Speech Recognition, Natural Language Processing, Best Next Action, and Time Series predictions

• Build solutions from identifying business problems, to collecting training dataset, to analyzing data, to modeling, to validating and to delivering production grade solutions at scale.
• Research latest related academic papers and test nascent ideas which can potentially solve new business problems and enhance existing solutions.
• Responsible for developing and defining deployment strategies for production quality AI solutions in Cloud infrastructure at scale
• Drive both high-level and detailed technical designs and conduct design reviews as needed
• Responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, and CI/CD tool integration
• Provide technical mentorship to team members at junior levels
• Actively participate in business and technical discussions and forums

We're building an AI-powered research platform for institutional investors. Our platform turns vast amounts of market, alternative, and proprietary data into actionable intelligence — powered by AI agents that depend on clean, reliable, real-time data to do their job.

We need someone to own data. Not manage a team that does data. Own it — from finding the right sources, to getting them flowing, to making sure they stay healthy at scale.

Today we ingest from hundreds of sources. That number is growing fast. The sources are diverse: real-time market feeds, regulatory filings, news, social sentiment, alternative datasets, and proprietary client data. Some are free APIs. Some are $10K/month enterprise contracts. Some are clients pushing their own data into our platform. Every one of them is different, and most of them will break in ways you don't expect.

You'll evaluate vendors, negotiate deals, build integrations, monitor quality, track costs, and make the call on what's worth paying for. When something breaks at 2 AM, you'll know why before the alert finishes firing.

This is an end-to-end ownership role. No handoffs.

Responsibilities

• Build and maintain integrations with a large and growing number of external data sources — APIs, WebSockets, file drops, streams, scrapers, and formats you haven't seen yet
• Evaluate and compare data vendors across quality, reliability, coverage, cost, and terms of service
• Negotiate contracts and manage commercial relationships with data providers
• Design and operate high-throughput ingestion pipelines handling mixed workloads (real-time, near-real-time, batch, event-driven)
• Build monitoring that tells you — before anyone else — when data is late, wrong, incomplete, or drifting
• Manage data quality at scale: anomaly detection, cross-source validation, schema drift detection, gap filling
• Handle both structured data (time-series, tabular) and unstructured data (documents, text, images) with appropriate extraction and storage
• Track costs per source, usage per consumer, and ROI — recommend what to keep, upgrade, or cancel
• Build tooling that makes adding the next data source faster than the last one
• Use AI tools aggressively in your daily work — for code generation, testing, documentation, anomaly analysis, and anything else that makes you faster

Requirements

You've done this before:

• 5+ years building data pipelines that run in production, 24/7, with real SLAs
• Deep hands-on experience with SQL databases and time-series data
• Python as your primary language, comfortable with async programming
• You've integrated with dozens of external APIs and dealt with the reality of unreliable vendors, changing schemas, rate limits, and bad documentation
• You've built monitoring and alerting for data systems — not as an afterthought but as part of how you work

You think about the whole picture:

• You don't just connect to an API. You think about what happens when it goes down, when the schema changes, when the data is wrong, when the bill doubles
• You understand that data has a cost and a value, and not every source is worth keeping
• You've worked with data vendors commercially — contracts, pricing tiers, usage negotiations

You use AI daily:

• AI coding tools are part of your workflow today, not something you're curious about
• You can articulate specifically how AI makes you faster and where it doesn't help
• You'd be frustrated if you couldn't use AI in your work

Nice to have

• Experience with financial market data
• Experience with streaming systems (Kafka or similar) at scale
• Vector database or embedding pipeline experience
• Experience with unstructured data extraction (PDFs, documents, NLP)

Perks & Benefits

• Senior individual contributor role with full ownership of the data domain
• Direct access to leadership — no bureaucracy, fast decisions
• AI tools provided and encouraged across all work
• Remote-friendly, async-first
• Compensation commensurate with experience

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

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

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

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

Responsibilities and Tasks

Product Quality (PQ) Predictive Solutions:

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

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

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

Agentic AI Development:

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

• Optimize for performance, latency, and token efficiency.

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

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

Software Engineering and Productionalization:

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

• Optimize system performance, latency, and token efficiency.

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

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

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

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

Required Qualifications & Skills

Education/Experience:

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

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

Technical Skills:

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

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

• Experience with SQL for data extraction and manipulation.

• Experience with version control (Git).

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

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

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

Preferred Qualifications

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

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

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

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

As a Senior Data Engineer, you will be working on:

• Translate data requirements from business users into technical specifications.

• Collaborate with partner agency’s IT teams on technology stack, infrastructure and security alignment.

• Build out data product as part of a data team:

• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems.

• Day-to-day monitoring of databases and ETL systems, e.g., database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence; ensure maximum database uptime;

• Construct, test, and update useful and reusable data models based on data needs of end users.

• Design and build secure mechanisms for end users and systems to access data in data warehouse.

• Research, propose and develop new technologies and processes to improve agency data infrastructure.

• Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures. • Maintain data catalogue to document data assets, metadata and lineage.

• Implement data quality checks and validation processes to ensure data accuracy and consistency.

• Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data.

What we are looking for:

• A Bachelor’s Degree, preferably in Computer Science, Software Engineering, Information Technology, or related disciplines.

• Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage.

• Demonstrated ability in using cloud technologies such as AWS, Azure, and Google Cloud.

• Experience with Databricks.

• Experience in designing, building, and maintaining batch and real-time data pipelines.

• Experience with orchestration frameworks such as Airflow, Azure Data Factory.

• Proficiency in working with Python, Shell Scripts, and SQL.

Preferred requirements:

• Familiarity with building and using CI/CD pipelines.

• Familiarity with DevOps tools such as Docker, Git, Terraform.

• Experience with implementing technical processes to enforce data security, data quality, and data governance.

• Familiarity with government systems and government's policies relating to data governance, data management, data infrastructure, and data security.

• Experience in Climate and Weather domains will be an advantage.

This will be a 2-years direct contract position.

Responsibilities

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

Requirements

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

Proficient in

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

Ethos Search Associates Pte. Ltd.

EA License No: 13C6655

EA Reg No: R1988580 Jacky Chong

Key Responsibilities

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

Preferred Qualifications

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

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

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

By sending us your personal data and curriculum vitae (CV), you are deemed to consent to PERSOL Singapore Pte Ltd and its affiliates to collect, use and disclose your personal data for the purposes set out in the Privacy Policy available at https://www.persolsingapore.com/policies. You acknowledge that you have read, understood, and agree with the Privacy Policy. 

PERSOL Singapore Pte Ltd

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

•Registration ID: Heah Sian Wei R23117518

Here’s a shorter, more attention-grabbing version:

⸻

JOB DESCRIPTION

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

JOB SUMMARY

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

ESSENTIAL DUTIES AND RESPONSIBILITIES

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

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

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

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

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

JOB QUALIFICATIONS & KNOWLEDGE REQUIREMENTS

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

• Strong statistics knowledge

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

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

• Good data sensitivity skill set is plus

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

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

• Strong team mentality, interpersonal and communications skills

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

EDUCATIONAL BACKGROUND & EXPERIENCE

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

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

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

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

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

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

Data Platform & Pipeline Engineering

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

Data Management, Quality & Governance

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

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

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

Requirements/skills

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

EA License No. 01C4394

By sending us your personal data and curriculum vitae (CV), you are deemed to consent to PERSOL Singapore Pte Ltd and its overseas subsidiaries and affiliates collecting, using and disclosing your personal data to prospective employers/companies based in any country for purposes of evaluating suitability for employment, conducting reference checks, administering employment related services and such other purposes stated in our privacy policy. Our full privacy policy is available at https://www.persolsingapore.com/. If you wish to withdraw your consent, please drop us an email to let us know. Please feel free to contact us if you have any queries.

Job Description:

We are seeking a talented and experienced Data Scientist to join our team. The ideal candidate will be passionate about utilizing data science methodologies to derive insights from digital device sensor data coming from clinical studies and contribute to the development and implementation of algorithms in this area. As a Data Scientist, you will work closely with customers to analyze data and build models and tools that enhance understanding of clinical outcomes and solve their business problems.

Responsibilities:

• Collaborate with customers to identify key questions, develop hypotheses, and test those hypotheses with clinical study data.
• Develop and implement machine learning algorithms for processing and interpreting sensor data (e.g., accelerometers, heart rate monitors, etc.). Research and develop novel digital measures with clinical significance.
• Apply data preprocessing techniques to optimize large sets of sensor data processing and analysis, handling issues like noise, missing data, and time-series synchronization.
• Validate and interpret results to ensure accuracy, performance and scalability in real-time processing of sensor streams.
• Communicate findings and insights to stakeholders through clear and compelling visualizations, reports, and presentations.
• Work closely with cross-functional teams to develop data-driven solutions to address business needs.
• Stay up-to-date with the latest advancements in data science and clinical research to continuously improve methodologies and approaches.

Requirements:

• Ph.D. in Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience in data science, with a focus on sensor data analysis or digital health.
• Strong understanding of time-series analysis, signal processing, and feature extraction techniques.
• Proficiency in programming languages and libraries (e.g, Python/R, TensorFlow/Pytorch) for data analysis and machine learning.
• Hands-on experience with big data platforms and tools (e.g., Hadoop, Spark, cloud environments).
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills with the ability to work effectively in a team environment.

Preferred Qualifications:

• Hands-on experience with Large Language Models (LLMs) or Generative AI projects, such as prompt engineering, fine-tuning, or implementing Retrieval-Augmented Generation (RAG) pipelines
• Familiarity with cloud-based deployment platforms such as AWS, Azure or related and their data pipeline development.
• Experience working in the healthcare or pharmaceutical industry, particularly in clinical trials or digital health devices.
• Proven experience in taking algorithms from research to production, including considerations for scalability, performance, and ease of integration.
• Understanding of clinical trial workflows and regulatory requirements related to digital health.

Asia-Pacific data centre Organization , backed by strong institutional investors, with a growing portfolio of hyperscale and enterprise-grade data centres across key regional markets.

Overview

The Contract Manager will be responsible for the administration, compliance, and commercial governance of contracts across data centre projects. This role ensures contractual obligations are managed effectively, risks are mitigated, and commercial and legal interests are protected throughout the project lifecycle.

Responsibilities

Contract Administration & Compliance

• Manage and administer main contracts, consultant agreements, and key subcontracts

• Ensure compliance with contract terms, conditions, and timelines

• Track contractual deliverables, notices, and obligations across projects

• Maintain accurate and auditable contract documentation

Change, Claims & Variations

• Manage variations, change orders, claims, and extensions of time

• Assess entitlement, support negotiations, and coordinate with legal advisors where required

• Ensure timely submission and response to contractual notices

Commercial & Risk Management

• Identify, assess, and mitigate contractual and commercial risks

• Support cost control and commercial reporting from a contractual perspective

• Assist in dispute avoidance and resolution strategies

Governance & Best Practice

• Support the development and enforcement of contract management standards and processes

• Contribute to continuous improvement of contract templates and governance frameworks

Requirements

• 8 years of contract / commercial management experience

• Proven experience on data centre, mission-critical, industrial, or large-scale infrastructure projects

• Experience working with developers, operators, or main contractors preferred
  

How to Apply: Click Apply now — or send your resume directly to Talent@BuildBridgePartners.com

EA Name: BuildBridge Partners Pte Ltd

EA License No: 25C2918

EA Reg No: R1551092

Khoo Yan Jie

Your new company

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

Your new role

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

What you'll need to succeed

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

What you'll get in return

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

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

What you need to do now

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

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

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

Here’s a shorter, more attention-grabbing version:

⸻