Data Engineer: Cloud Analytics & AI Solutions Lead

ABEAM ANALYTICS PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

ABEAM ANALYTICS PTE. LTD. seeks a Data Engineer to design, develop, and support enterprise data platforms and cloud-native architectures. You will work on analytics applications, AI-enabled solutions, and pre-sales engagements to transform data into actionable business insights.

Responsibilities include building scalable data pipelines, data warehouses, and analytics-ready datasets, while applying NLP and ML fundamentals to extract value from diverse data sources for enterprise clients.

Qualifications

• Design, develop and maintain scalable enterprise data platforms.
• Build ETL/ELT pipelines and analytics-ready datasets.
• Apply NLP, ML fundamentals, and AI approaches to data analysis.
• Collaborate with stakeholders to translate requirements into solutions.
• Prepare architecture recommendations and solution demonstrations for pre-sales.

Responsibilities

• Design, develop, and maintain scalable enterprise data platforms and data warehouses.
• Build and optimise ETL/ELT pipelines and data integration frameworks.
• Develop analytics apps using cloud data platforms and visualization tools.
• Apply NLP, ML fundamentals, and AI approaches to extract insights from data.
• Lead solution presentations, architecture walkthroughs and PoC reviews.
• Collaborate with clients to design and deliver data, analytics and AI solutions.
• Support pre-sales with proposals, estimates and architecture recommendations.

Skills

Data Engineering

ETL/ELT Development

Data Integration

Data Warehousing

Data Modelling

SQL Development

Cloud Data Platforms

Analytics Applications

AI/ML Fundamentals

NLP Basics

Tools

Microsoft Fabric

OneLake

Databricks

AzureData Factory

Power BI

SAP Datasphere

SAP HANA

SAP Joule

Job description

ABEAM ANALYTICS PTE. LTD. seeks a Data Engineer to design, develop, and support enterprise data platforms and cloud-native architectures. You will work on analytics applications, AI-enabled solutions, and pre-sales engagements to transform data into actionable business insights.

Responsibilities include building scalable data pipelines, data warehouses, and analytics-ready datasets, while applying NLP and ML fundamentals to extract value from diverse data sources for enterprise clients.