Lead Data Engineer

In this role you will translate business challenges into data-driven insights that improve performance for Electricity Transmission. You will partner with stakeholders to define requirements and deliver end-to-end data products and dashboards on cloud platforms, with a focus on Azure. You’ll manage the full software lifecycle, including CI/CD, testing, and deployment, while ensuring data quality and a single source of truth. You will work on AI-enabled automation and data pipelines to drive actionable outcomes. This is a hands-on opportunity to shape how data unlocks value across the business and support the energy transition mission.

• Understand business challenges and translate them into data requirements and insights
• Develop ETL processes for data insights platforms
• Collaborate with ET teams to assess data quality and influence data models and architecture
• Lead installations and patches for the insight platform and support developers/stakeholders
• Support data flow and mapping for IT project solutions
• Produce documentation from requirements to delivery
• Ensure data quality and single source of truth across pipelines
• Design, implement and maintain CI/CD pipelines and test frameworks for data pipelines and dashboards
• Implement monitoring, logging, and observability for data pipelines and dashboards
• Collaborate with ML/agentic automation teams to integrate automated workflows
• Apply ORM and database design principles in data models
• Maintain data fabric/lake/warehouse design and promote data governance across the business
• Provide operational support for AI agents and monitor performance
• Identify opportunities for AI-driven process improvements
• Maintain AI agent knowledge bases and configurations
• Ensure compliance with governance, security, privacy, and regulatory requirements
• Support testing, validation and deployment of AI features
• Analyze user feedback and performance data to optimise AI solutions
• Drive continuous improvement of AI effectiveness and user experience
• Support safe deployment of AI capabilities across the organisation

• Delivering business benefits through data products and dashboards from requirements to deployed solutions
• CI/CD for data platforms and analytics applications
• Software development life-cycle practices (version control, code review, testing, release management)
• Knowledge of agentic LLMs or automation frameworks and safe production integration
• ORM concepts and applying them in data models and service layers
• Strong analytics and dashboarding experience (Power BI)
• Hands-on experience with Snowflake and/or Azure (Synapse, ADLS, Azure SQL, Azure Data Factory)
• Stakeholder engagement to define KPIs, SLAs, and data contracts
• Familiarity with DBT, DataOps and modern transformation tooling
• Experience supporting digital products, automation platforms, AI solutions, or enterprise applications
• Understanding of Generative AI, LLMs, AI agents, and conversational AI
• Analytical and problem-solving abilities for complex issues
• Translating business requirements into technical solutions
• Knowledge of data governance, information security, and responsible AI
• Agile delivery experience

• collaboration
• problem-solving
• communication
• Power BI
• Snowflake
• Azure (Synapse, ADLS, Azure SQL, Data Factory)