Lead Data Engineer

The Government Digital Service (GDS) is the digital centre of government. We are responsible for setting, leading and delivering the vision for a modern digital government.

Our priorities are to drive a modern digital government, by:

1. joining up public sector services
2. harnessing the power of AI for the public good
3. strengthening and extending our digital and data public infrastructure
4. elevating leadership and investing in talent
5. funding for outcomes and procuring for growth and innovation
6. committing to transparency and driving accountability

We are home to the Incubator for Artificial Intelligence (I.AI), the world-leading GOV.UK and at the forefront of coordinating the UKs geospatial strategy and activity. We lead the Government Digital and Data function and champion the work of digital teams across government.

Were part of the Department for Science, Innovation and Technology (DSIT) and employ more than 1,000 people all over the UK, with hubs in Manchester, London and Bristol.

The Government Digital Service is where talent translates into impact. From your first day, youll be working with some of the worlds most highly-skilled digital professionals, all contributing their knowledge to make change on a national scale.

Join us for rewarding work that makes a difference across the UK. You'll solve some of the nations highest-priority digital challenges, helping millions of people access services they need

Youll be the technical data engineering lead for the data and analytics team in the Digital Identity (DI) programme.

As a Lead Data Engineer youll:

• be responsible for the data and analytics teams data engineering strategy; transforming Digital Identity data into structures and layers that enable analysis
• work with stakeholders and teams across the Digital Identity programme to understand relationships between data and business processes; use this to define data requirements; and translate these into data structures and data models that resolve specific business problems for analysis
• proactively identify and integrate cutting-edge tools and techniques to ensure our data analytics infrastructure remains scalable and future-proof
• collaborate with Data, Solution, and Enterprise Architects to ensure all data engineering strategy, pipelines, and architecture designs adhere to GDS and DSIT documentation, standards, and enterprise principles
• lead a team of analytics engineers, data modellers and data engineers to design, build and maintain data models which enable analysis through reproducible pipelines
• act as a bridge between technical teams, business stakeholders, and senior leadership, ensuring analytics capabilities align with strategic objectives and operational requirements
• design and optimise metadata repositories, establishing the standards for how the analytics teams store, categorise, and utilise data to ensure long-term discoverability and consistency

Were interested in people who:

• are accomplished expert data engineers with experience of producing, maintaining and updating data models which solve business problems and are optimised for data analysis
• have extensive experience using and managing Google Cloud and AWS, using technologies such as Redshift, BigQuery, Dataform, and SQL; and using their experience to continuously improve the codebase and reliability of solutions
• have experience transforming complex unstructured data into structures and layers that enable analysis, defining and promoting best practices for creating repeatable, reliable and reusable data solutions that therefore drive impact and value
• can listen to and interpret the needs of technical and non-technical stakeholders, manage their expectations and influence in order to gain the confidence of senior leaders
• have experience at a senior level of providing technical leadership, guiding and mentoring engineering teams