Data and AI Engineer

The Data & AI Engineer is responsible for establishing and managing the organisation's enterprise data platform, data architecture, data, reporting, integration, governance and AI capabilities, transforming fragmented business data into trusted information assets that enable decision-making, automation, analytics and future AI-driven business outcomes.

A key responsibility of the role is to establish the organisation's foundational data architecture, including data models, master data, governance frameworks and semantic layers. The role will consolidate information currently distributed across multiple business applications into a trusted enterprise data platform that supports reporting, analytics, automation and future AI capabilities. The position will also assess how users should interact with information, determining where traditional reporting solutions such as Power BI dashboards are appropriate and where AI-enabled conversational experiences leveraging semantic models can provide greater business value. Working closely with business stakeholders, the Business Applications Specialist and Business Analyst, the role translates business information requirements into data solutions that improve visibility, support decision-making and drive business performance.

As the technical owner of the Digital Business Enablement pillar's data, analytics and AI capabilities, the role will lead the development of the organisation's data platform, reporting frameworks, system integrations, automation opportunities and AI initiatives.

The position plays a critical role in transitioning the organisation from fragmented reporting and siloed data to a modern data-driven operating model that supports strategic planning, operational management and continuous improvement.

This is a hands on role.

You will lead the architecture and development of a new data landscape from scratch. This would involve understanding varied business applications, the data they hold, and key business requirements that would enable you to prepare conceptual, logical and physical data model. You will need to implement the database with this schema and build integrations and data pipelines to populate it. You will also own, understand and develop the reporting layer using traditional reporting platforms such as PowerBI and innovative solutions by building semantic models and development of agents.

Technical Skills:

• Data modelling and Data Architecture
• ETL/ELT development
• Data pipeline design and management
• Data transformation and integration
• Data quality management
• Database design, development and administration
• Data visualisation and reporting with PowerBI
• Self-service reporting solutions
• Significant Experience with atleast one Data and Analytics Platforms such as Fabric, Snowflake, Databricks
• Power Platform
• Working with middleware products such as ADF, Boomi, Workato
• Experience developing agents on Microsoft copilot studio or other Agentic platforms
• Establishing Prompt Engineering concepts
• Data and AI Governance