Lead Data Engineer

As Lead Data Engineer in National Grid’s Electricity Transmission team, you will steer data engineering direction for scalable data products that support the journey to Net Zero. You’ll own engineering standards, patterns and the end-to-end lifecycle of governed data pipelines used for BI, KPI reporting, and analytics workloads. You’ll collaborate with engineers and stakeholders to turn business challenges into impactful data solutions and mentor the broader data engineering community. This is a product-focused role that values reliability, security, and continuous improvement to drive tangible energy-transition outcomes.

• 26 days holiday
• annual performance incentive
• pension scheme (double matched up to 6%)
• life insurance
• Private Medical Insurance contribution
• share incentive plan; salary sacrifice schemes; EAP; matched charity giving

• Lead the design, build and delivery of data pipelines to support performance goals
• Set and enforce engineering standards including patterns, code reviews, testing, CI/CD and deployment practices
• Mentor and develop data engineers across the team and community
• Own data product implementations and ensure business readiness and ongoing improvement
• Shape target-state architecture with architects and define integration, data modelling and non-functional requirements
• Own data governance and data quality frameworks and ensure policy compliance during development and operation
• Analyze insights to identify trends and propose actions to improve business outcomes
• Manage the data product lifecycle and ensure the data roadmap remains relevant and actionable

• Demonstrable experience leading a data engineering team or workstream with technical direction
• Experience in stakeholder engagement and translating business challenges into data solutions
• Experience with data mining, data profiling, and ETL development for data quality and analysis
• Experience in data development environments and risk/controls awareness
• Working knowledge of modern data architecture patterns (data mesh, data fabric, Lakehouse)
• Knowledge of SQL, Python (essential); C# (desirable) and data transformation tools such as DBT, Microsoft ADF
• Experience with Snowflake, Microsoft Fabric, Promethium, and data visualization tools (Power BI, Tableau)
• Version control and CI/CD for data pipelines (Git, )
• Certifications in data/AI workloads (e.g., Azure Data Engineer Associate) is a plus

• Stakeholder management
• Collaborative problem solving
• Communication and business readiness assessment
• SQL
• Python
• C#