Data Engineer

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.