Senior Program Manager - Data

Our Client is a UK based Financial Services business embarking on an enterprise wide transformation programme. This key appointment will focus on the critical data focus programmes within the portfolio.

3 Day per week in Wiltshire.

Project scoped outside IR35

Rate: £800 - £1,000 per day.

KEY RESPONSIBILITIES

Program Delivery & Leadership

• Lead the end-to-end delivery of the Data transformation programme
• Identify a number of value-driven use cases to focus delivery in 2026 with a multiple waves to deliver thereafter. Ensure use case business cases are developed and are used to prioritise delivery
• Carry out a review of the delivery approach based on a conceptual model that identified some 60 KDEs (Key Data Entities) and assess the best approach for ETL, data modelling and the creation of a gold reporting layer. Align the implementation of the KDEs with identified use cases
• Drive the Databricks migration programme, including data Lakehouse transformation
• Working with Design Authority stakeholders, make critical decisions on technology choices and processes
• Build a Roadmap for delivery and identify resource requirements
• Transition the programme from fully outsourced to potentially hybrid or insourced model
• Manage the handover and knowledge transfer from third-party consultancy to internal teams
• Ensure best practice programme management disciplines are employed in the delivery of the programme. This includes programme charter, roadmap with clearly defined objectives, planning, dependencies, financials, cross-functional teams, management of RAID logs, reporting, governance, escalations etc. ensuring that outcomes are delivered on time and quality

KEY SKILLS & COMPETENCIES

Technical Background

• Data expertise: strong understanding of data platforms, pipelines, ETL/ELT processes, data engineering, integration, analytics and modern data tooling
• Data Architecture: strong understanding and experience of cloud data architecture and design patterns for building a data Lakehouse
• Data Science & Analytics: Sufficient understanding to validate whether data models support ML/analytics use cases
• Data Governance: Experience of data governance, data quality frameworks, and data management practices