Police and Public Protection Technology Portfolio (PPPT) Overview
The Police and Public Protection Technology Portfolio (PPPT), part of Home Office Digital delivers digital solutions for policing and public protection. Serving all UK police forces and over 20 law enforcement agencies, PPPT designs, builds, and supports major transformation programmes like NLEDP and HOB. It also maintains critical systems such as the Police National Computer (PNC) and Police National Database (PND), and leads infrastructure upgrades like LECN and LECP.
Within PPPT, the National Communications Data Service (NCDS) ensures communications data is accessible and operationally valuable amid ongoing technical and business change.
Responsibilities
In this role, you will translate strategic data vision into tangible designs and solutions, ensuring data assets are secure, well-structured, and aligned with evolving Home Office priorities. Partnering with Technical Architects, Principal Data Architects, and various data teams, you will evaluate existing platforms, identify gaps, and recommend optimisations, whether via cloud-native services, big data-based ecosystems, or modern data warehouses.
You’ll oversee how data dictionaries, metadata systems, and governance frameworks are implemented, championing best practices across multiple programs. By leading data design reviews, you’ll ensure alignment with department-wide standards, while also balancing performance, scalability, and compliance needs.
Additionally, you will serve as a trusted advisor to senior stakeholders, translating business requirements into actionable architecture patterns and reference models. You will collaborate with and guide multiple stakeholders on data-centric initiatives in the Home Office.
You’ll also mentor less-experienced data architects, sharing emerging trends in big data technologies and building a resilient, future-proof data estate.
Ultimately, your expertise will help streamline Home Office workflows, promote consistent data usage, and foster innovative ways to harness critical data at scale.
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