My Contribution

Defining Future-State Platform Capabilities

My role is to translate the programme’s strategic objectives, emerging use cases and technical considerations into clear future-state platform capabilities, features and high-level requirements.

Working across architecture, engineering, security, data governance and AI governance, I bring structure to complex and sometimes ambiguous areas. My focus is on defining what the platform needs to enable while keeping requirements sufficiently solution-agnostic to preserve architectural flexibility and avoid prematurely prescribing the implementation.

My work spans four connected areas:

01 Agentic Access & Governance

For the emerging agentic access model, I translated business, operational and governance needs into a structured set of future-state platform capabilities. These covered agent identity and ownership, authentication and authorisation, delegated authority, access boundaries, human oversight, observability, auditability and accountability.

I brought together architecture, engineering, operations, security, data governance and AI governance stakeholders through workshops and playback sessions. I challenged assumptions, identified gaps and overlaps, clarified ownership boundaries and structured the resulting needs into capabilities, features, user stories, acceptance criteria and behavioural scenarios. This created an implementation-agnostic framework to inform roadmap planning, solution design and future delivery.

02 Data Product Access Discovery

The Data Product work focused on establishing a shared understanding of how enterprise Data Products should be defined, discovered, accessed, consumed and governed. I explored ownership, metadata visibility, governance controls, maturity thresholds, access entitlements, authorisation boundaries and approval responsibilities.

I consolidated agreed definitions, stakeholder perspectives, assumptions, dependencies, risks and unresolved design questions into structured discovery and current-understanding artefacts. These clarified how Data Products should be represented, governed and accessed, providing platform engineering and infrastructure teams with a shared foundation for implementing the tables, metadata, entitlements and supporting controls needed for secure downstream consumption.

03 Platform Performance & Cost

I assessed the platform’s future performance and cost-management needs by establishing the problem statement and documenting the existing operating context, pain points and risks. The analysis covered performance and scalability, compute and storage costs, monitoring and observability, and workload and capacity management.

Through workshops with platform engineering, architecture, infrastructure, cloud operations and FinOps stakeholders, I mapped the findings into high-level capabilities, supporting features, user stories and acceptance criteria. I prioritised these requirements according to the risks and pain points they addressed, creating a solution-agnostic foundation for future platform design and delivery decisions.

04 Streaming

I examined how the future platform could support streaming alongside batch processing without creating divergent data paths, duplicated processing or inconsistent standards. The existing platform primarily supported batch workloads, with streaming handled through bespoke solutions, creating risks around data freshness, representation, governance, and consistent downstream consumption.

Working with platform architecture, data engineering, infrastructure, operations and governance stakeholders, I documented the current state, risks and pain points before mapping them into future-state capabilities, features, user stories and acceptance criteria. These covered unified data flows across batch and streaming, flexible arrival patterns, batch and continuous runtime models, consistent failure and recovery, end-to-end observability, and common governance standards. The resulting requirements gave architects a solution-agnostic basis for assessing implementation options and making architectural decisions about how streaming capabilities should be introduced into the platform.