Lead Data Engineer – Hybrid, DaaS & Data Platforms

National Highways; Manchester; Hybrid; GBP 75,000 - 110,000; Full time

Job summary

National Highways is strengthening its Data Team by recruiting Lead Data Engineers to design, deliver data products across the transport network, in a hybrid role with two days in the office.

You will work with stakeholders to build data pipelines and governance, enabling trusted analytics with enterprise solutions such as Databricks, Power BI and ThoughtSpot, while ensuring production data services remain reliable and cost efficient.

Qualifications

• Experience leading data engineering teams and delivering data products.
• Strong ability to translate stakeholder needs into scalable data solutions.

Responsibilities

• Deliver the Data as a Service (DaaS) roadmap by onboarding enterprise data and expanding analytics capabilities.
• Design, build and enhance data pipelines and reusable data assets across transactional, asset, traffic, event and business data.
• Collaborate with stakeholders to understand analytical and reporting needs, develop user stories and deliver trusted data products for operational and strategic decisions.
• Embed data governance, quality and assurance across the data lifecycle, including metadata management.
• Support operation and continuous improvement of production data pipelines and platform capabilities for reliability and cost efficiency.
• Promote best practices, automation, testing and governance across development lifecycles.

Skills

Stakeholder management

Leadership

Analytical thinking

Problem solving

Tools

Databricks

Power BI

ThoughtSpot

Python

SQL

Azure Cloud

Azure Data Factory

Unity Catalog

Job description

National Highways is strengthening its Data Team by recruiting Lead Data Engineers to design, deliver data products across the transport network, in a hybrid role with two days in the office.

You will work with stakeholders to build data pipelines and governance, enabling trusted analytics with enterprise solutions such as Databricks, Power BI and ThoughtSpot, while ensuring production data services remain reliable and cost efficient.