Data Engineer / Data Analyst

L M Foundation Specialist · Singapore

Sector
Data & Analytics
Function
Product & Engineering
Level
Junior
Employment type
Full Time
Posted
2026-05-15
Source
mycareersfuture

Duties & Responsibilities:Collect, clean, and organise data from construction projects, including progress, manpower, equipment, productivity, and costsMaintain and manage structured databases and datasets for operational and project reportingPrepare regular reports, dashboards, and data visualisations for management reviewSupport analysis of project productivity, costs, resource utilisation, and overall project performanceAssist in implementing and improving digitalisation, automation, and AI-driven reporting or analytics processes within construction operationsSupport the adoption of AI tools and data-driven solutions to improve operational efficiency and decision-makingCoordinate with project teams, engineers, and management to ensure accurate and timely data collectionPerform any other ad hoc duties as assignedRequirements:Diploma or Degree in Data Analytics, Data Science, Computer Science, Engineering, Construction Management, or related fieldsEntry-level candidates and fresh graduates with a strong interest in the construction industry, digitalisation, and AI applications are welcome to applyCandidates with experience in construction analytics, AI tools, automation, Power BI, Python, or digital transformation initiatives will have an added advantageBasic knowledge of SQL and Microsoft Excel (PivotTables, formulas, and data analysis functions)Familiarity with dashboarding or visualisation tools such as Power BI or Tableau is preferredAble to work in a fast-paced environment with good coordination, analytical thinking, and problem-solving skillsGood communication and interpersonal skills, with the ability to work effectively with cross-functional project teamsCandidates able to start within short notice will have an advantage

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Data & Analytics Digital Transformation Machine Learning Liaising with cross functional teams Operational Efficiency Microsoft Excel Construction Big Data