Develop and maintain scalable and efficient Big Data platform components and OLAP engines.
Collaborate with cross-functional teams to integrate new features and technologies.
Ensure the reliability and performance of our data infrastructure.
Troubleshoot and resolve complex technical issues.
Continuously improve system architecture and design for optimal performance.
Manage one of the Data Suite products, including but not limited to Data Map, Data Integration, Data Development, Data Management, Data Quality, Data Services, Data Metrics, Data Visualisation, etc.
Responsible for requirements analysis, product design, product prototyping as well as product operation.
Understand user needs and big data use cases, abstract complex requirements or scenarios into solutions, and implement them in the product to empower users.
Develop and maintain user relationships and communication channels with users, synthesize product features from users’ requirements and feedback.
Explore and continuously learn the best practices from the big data industry, and continuously plan the product blueprints in the long term.
Build data warehouses, real-time computing systems, and statistical analytics solutions for massive volumes of business data. Responsibilities include clarifying data logic, developing data tools, and optimizing workflows.
Participate in business performance analysis and provide data-driven insights and analytical methodologies to support product iteration.
Contribute to the development of big data service platforms, providing data services for online business scenarios such as querying, estimation, computation, and configuration.
Apply technologies such as stream processing and OLAP engines to modernize traditional business processes, improve the efficiency of data processing and utilization, and empower the business with deeper data insights.
Explore the application of AI technologies—including large language models (LLMs), agents, and retrieval-augmented generation (RAG)—in the data domain. Promote AI-driven data development and governance practices to enhance the intelligence and automation of data management.
In a data-driven and evaluation-driven manner, build an efficient closed loop for data iteration and establish an end-to-end data system spanning data sourcing, labeling, processing, synthesis, and evaluation. Continuously build high-quality datasets and evaluation sets to keep improving foundation model capabilities and to drive the development of AI models and applications.
Responsibilities cover one or more of the following directions:
Design and implement high-performance, scalable, and distributed data infrastructure covering the full lifecycle — data storage, ingestion, cleaning, labeling, management, and analysis — and continuously improve data engineering efficiency.
Design audio-visual multimodal training data strategies; develop efficient data processing, synthesis, and optimization operators and pipelines, and build a multimodal data asset repository to meet the data needs of large model development.
Build a "data–model–evaluation" closed loop together with Agents, using data to drive rapid iteration of large models.
Track cutting-edge techniques and methods in the large-model data domain, explore innovative approaches such as data augmentation, dat
Partner with Warehouse Operations, Planning, and Regional teams to provide actionable insights on key Warehouse metrics, not limited to productivity, performance and inventory health.
Monitor and deep dive into operational Key Performance Indicators to identify performance gaps and root causes.
Translate operational business requirements into structured technical solutions and scalable data workflows.
Automate manual operational reporting processes using SQL, Python, VBA, or other tools.
Develop and maintain dashboards and monitoring systems to ensure data accuracy and timeliness.
Optimise end-to-end reporting flow from data source (WMS / order system) to front-end dashboards.
Support warehouse-related initiatives such as process optimisation, capacity planning, liquidation analysis, and cost efficiency projects.
Perform ad-hoc deep dives to support urgent operational issues and drive data-backed decision-making
Work closely with local teams to drive end-to-end BI projects across multiple markets, coordinating stakeholders from different business functions to ensure timely and successful project delivery
Define and maintain key business performance metrics across the region, partnering with senior management and local business teams to drive alignment on KPI definitions and reporting methodologies, ensuring consistency and comparability across markets
Develop and maintain interactive dashboards and reports to provide visibility into business performance
Leverage both technical expertise and business understanding to perform analysis, generate insights, and influence strategic decisions
Develop executive-ready presentations and data-driven storytelling materials that effectively communicate complex analyses, business insights, and strategic recommendations to senior management and key stakeholders
Lead regional workplace AI adoption initiatives by identifying high-impact use cases, promoting best practices, and driving the integration of AI-powered tools into daily business processes to improve productivity and operational efficiency
Conduct in-depth research across industries and companies, analysing market developments, competitive dynamics, financial performance, and emerging trends
Gather and triangulate data from internal teams, industry reports, company disclosures, databases, and primary research
Analyse complex datasets to uncover trends and generate actionable insights for decision-making
Translate research findings and analysis into clear, concise reports and presentations for senior stakeholders
Maintain research databases and knowledge resources to ensure insights and data remain current and accurate
Currently pursuing or has completed a Bachelor's Degree in any discipline from a reputable university with strong academic credentials. Candidates who are currently pursuing their Bachelor’s Degree should be expected to graduate by Dec 2026, and all candidates must be able to join us by Jan 2027.
Candidates who meet the above requirements and are currently pursuing a Master’s Degree or above must be able to join us on a full-time basis by Jan 2027. A Master’s Degree or above is advantageous but not required.
Prior experience in equity research, asset management, strategy consulting research, or in-house corporate development and strategy, internship or full-time.
Experience in the consumer internet sector is a plus.
Excellent research, data analysis and problem-solving skills
Strong written and verbal communication skills.
Ability to work independently and as part of a team.
Highly driven and hard-working self-starter, focused on delivering high quality results with efficiency and speed
Genuine passion for continual self-development in a dynamic company
Develop Data Center strategies that are aligned with business needs, including capacity planning, cost modeling, and lifecycle management.
Drive the evaluation of commercial terms, estimate market trend, and calculate total cost of ownership (TCO) for new and existing data center contracts.
Collaborate with internal stakeholders (e.g., Technical Project Managers, Data Center Operations, Network Engineering, Finance, Procurement, Legal etc.) to execute Data Center strategies and structure commercial agreements.
Work closely with engineering and operations teams to ensure commercial and technical alignment during data center planning and deployment phases.
Conduct research and provide market insights and analysis on data center trends, pricing models, and emerging technologies to support business decisions.
Coordinate with colocation providers, equipment vendors, and system integrators to ensure optimal performance and commercial value.
Participate in vendor evaluations for capacity acquisition, contract negotiations, and performance reviews.
Support the development of partnership strategies to enhance service quality and reduce cost exposure.
Track and analyze key metrics related to cost efficiency, uptime, and resource utilization, and assist in preparing summary reports for management.
Maintain dashboards for monitoring data center expenditures, electricity cost trends, forecast accuracy, and vendor performance.
Continuously working in process improvement plans to streamline contract negotiations and execution.
Contribute to initiatives aimed at standardizing commercial processes and documentation across regions.
Support continuous improvement in financial governance, vendor accountability, and project delivery.
Identify opportunities for process improvement and cost optimization in collaboration with senior team members.
Established in 2010, Vinova is a passion-driven and award-winning development company for mobile, web, and enterprise applications. Our clients span the globe and cover a wide range of projects including IoT, blockchain, banking, fintech, networking, and ecommerce. Vinova earns respect from customers by being committed to quality, flexibility, and speed. We strive to build great products by working with a passion, working closely with our customers, and through open but disciplined collaboration. You will be working in an encouraging and challenging environment, taking advantage of the latest technology to develop excellent mobile apps for clients. You will be engaging clients in both on-site and off-site support. Interested to join our all-star team? Submit your application to us now! Tell us why you want to work with us and why you think you’d be a good candidate. We are looking forward to hearing from you!
Job Summary
We are seeking a highly motivated and experienced Data Engineer (up to Senior Consultant level) to join our team for a major Government project. The ideal candidate is not just a data developer but a technical strategist who shares a strong conviction in the Government’s mission to serve the public through robust digital infrastructure. You will play a critical hybrid role, combining deep data engineering expertise with DevOps and cloud infrastructure capabilities to deliver secure, scalable, and impactful data solutions.
