Data Engineer

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

Overview

We are seekinga Data Engineer to design, develop, and support enterprise data platforms,cloud-native data architectures, analytics applications, and AI-enabledsolutions. The role combines hands-on data engineering, solution consulting,client engagement, and pre-sales activities to help organisations transformdata into meaningful business information and digital transformation outcomes.

Key Responsibilities

• Design, develop, and maintain scalableenterprise data platforms, data warehouses, data marts, and cloud-native data architectures.
• Build and optimise ETL/ELT pipelines,data-integration frameworks, and analytics-ready datasets from structured,semi-structured, and unstructured data sources.
• Develop and implement techniques and analyticsapplications to transform raw data into meaningful information usingdata-oriented programming languages, cloud data platforms, and visualisationsoftware.
• Apply data mining, data modelling, naturallanguage processing (NLP), machine learning fundamentals, and AI-enabledapproaches to extract and analyze information from large structured andunstructured datasets.
• Design and implement data-processing frameworksthat support analytics, reporting, AI-enabled applications, and businessdecision-making.
• Visualise, interpret, and report data findings,including the creation of dynamic data reports where required.
• Implement data-quality controls, governanceprocesses, monitoring frameworks, performance optimisation, andproduction-support activities across enterprise data ecosystems.
• Gather and analyse business and technicalrequirements through workshops, stakeholder-engagement sessions, andsolution-design discussions.
• Collaborate with business and technicalstakeholders to translate requirements into scalable data, analytics, AI, anddigital-transformation solutions.
• Prepare and deliver solution presentations,technical demonstrations, architecture walkthroughs, proof-of-concept reviews,and implementation recommendations for business and technical stakeholders.
• Lead and participate in client workshops,architecture discussions, technology assessments, feasibility studies, andproof-of-concept initiatives.
• Prepare solution proposals, RFP/RFQ responses,effort estimates, architecture recommendations, and supporting materials forpre-sales and business-development activities.
• Partner with clients across public sector,government agencies, education, financial services, manufacturing, trading, andenterprise sectors to design and deliver data, analytics, AI, anddigital-transformation solutions.

Technical Skills

• Data Engineering; ETL/ELT Development; DataIntegration; Data Warehousing; Data Mart Design; Data Modelling
• SQL Development; Database PerformanceOptimisation; Data Quality Management; Data Governance
• Analytics Applications; Data Mining; NaturalLanguage Processing; Machine Learning Fundamentals; Large Language Models
• Microsoft Fabric; OneLake; Databricks; AzureData Factory; Power BI
• SAP HANA; SAP Business Data Cloud; SAPDatasphere; SAP Databricks; SAP BTP; SAP Joule

Additional Advantages

• Experience with SAP data ecosystems, includingSAP HANA, SAP Business Data Cloud, SAP Datasphere, SAP Databricks, SAP Joule,SAP BTP, and SAP S/4HANA integrations.
• Exposure to emerging technologies such asGenerative AI, Agentic AI, intelligent automation, Large Language Models, andblockchain-enabled business solutions.
• Experience supporting public-sector andgovernment digital-transformation initiatives.
• Experience providing PMO support, projectgovernance, stakeholder management, project planning, risk and issuemanagement, resource coordination, and status reporting across technologyimplementation programmes.

Ideal Profile

• Strong foundation in data engineering, clouddata platforms, and enterprise analytics solutions.
• Able to bridge data engineering, analytics, AI,and consulting responsibilities while maintaining a hands-on engineering focus.
• Comfortable engaging clients, facilitatingworkshops, and presenting technical solutions to both business and technical stakeholders.
• Experience across project delivery, solutiondesign, proof-of-concept development, and pre-sales activities.
• Familiarity with SAP data ecosystems andemerging AI technologies is highly desirable.