Platform Specialist – Data & Analytics

About the Role Key Responsibilities Act as a hands-on platform specialist across a secure, cloud-based data and analytics platform. Contribute directly to build, configuration, and implementation activity alongside developers and data engineers. Support definition of the POC scope, success criteria, and value proposition. Shape the technical path from POC to MVP, considering scalability, security, governance, and reuse. Contribute to analytics and insight generation over identity, access, and entitlement-related datasets. Provide pragmatic technical input across data ingestion, analytics, visualization, access control, and environments. Work closely with delivery leadership to surface risks and maintain delivery momentum. Ensure decisions, progress, and artefacts are shared and transparent. Explain technical concepts clearly to technical and non-technical stakeholders. Enable teams to deliver independently over time. Technical Environment & Tooling (Indicative) The platform provides a secure, cloud-hosted analytics workbench supporting modern analytics and      data science workflows, including: Notebook-based development environments (Python / R style workflows)- SQL-based querying      and data transformation Dashboarding and visualization tools (e.g. Tableau, Power BI, Apache Superset or      equivalent)- Cloud-native infrastructure (e.g. AWS-based environments) Secure multi-user collaboration with governance and auditability Requirements Essential Experience- Active SC clearance.- Strong hands-on experience with cloud-based data and analytics platforms. Background in data engineering, analytics platforms, or data science enablement. Proven experience contributing directly to build and implementation. Experience taking initiatives from POC to MVP or production. Understanding of security, governance, reuse, and scalability considerations. Ability to simplify complexity and communicate technical trade-offs clearly. Desirable Experience: Experience working in secure or regulated environments. Exposure to analytics or data platforms involving identity, access management, or security-related      datasets. Experience enabling multiple teams or user groups on a shared platform. Track record of demonstrating business value early.