Data Engineer

Abeam Analytics; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

Abeam Analytics in Singapore seeks a Data Engineer to design, develop, and support enterprise data platforms, cloud-native data architectures, analytics applications, and AI-enabled solutions.

You will collaborate with stakeholders, build ETL/ELT pipelines, apply NLP/ML concepts, and deliver demonstrations and PoCs for pre-sales and client workshops.

Qualifications

• Experience designing scalable data platforms and analytics applications.
• Strong ability to translate business requirements into data solutions.
• Proficiency with cloud-based data architectures and data governance.

Responsibilities

• Design, develop, and maintain enterprise data platforms and data warehouses.
• Build ETL/ELT pipelines and analytics-ready datasets from varied data sources.
• Apply ML, NLP, and AI techniques to extract insights from large datasets.
• Collaborate with stakeholders to translate requirements into scalable solutions.
• Prepare solution demos, architecture walkthroughs, and PoCs for clients.

Skills

Data engineering

ETL/ELT development

Data integration

Data warehousing

Data modelling

SQL development

Data governance

Data quality

Machine learning

NLP

LLMs

Microsoft Fabric

Databricks

Azure Data Factory

Power BI

SAP HANA

SAP Datasphere

SAP Joule

AI technologies

Tools

Databricks

Power BI

Azure Data Factory

SAP Datasphere

SAP Joule

SAP HANA

OneLake

Microsoft Fabric

SAP BTP

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.