Senior Manager, Solution & Data Architecture

Reports to:

Global Director, Data, AI & Architecture Team: 4 data, AI and solution architects

Location:

London The role

We are looking for a Senior Manager, Data & AI Architecture to lead a team of four data, AI and solution architects and to act as the design authority for Pandora's data and AI platform. It is a dual role: you will set architectural direction and standards, and you will stay close to the technical work — reviewing and approving the designs that come through them.

Our target architecture is Databricks — Delta Lake, medallion patterns, Unity Catalog — with Azure Synapse and its conformed enterprise models still carrying a significant part of the estate. That estate supports supply chain, commerce, manufacturing, corporate tech and omni-channel. Leading the move onto Databricks, deciding where ownership sits as it goes, and keeping existing solutions coherent and supported while it happens, is the substance of the job.

The split is roughly 60% architecture, 40% leading and developing the team. Both are real; neither is a title.

Scope and authority

Design authority for Data & Analytics: approves data and AI solution designs, and can require rework, attach conditions to an approval, or withhold approval.

Chairs the architecture review forum, setting its standards, cadence and quality gates, and deciding what requires review against what is already covered by an approved pattern.

Resolves conflicting design positions across architects, lead engineers and delivery teams.

Owns reference architectures, solution patterns, data contracts and architecture decision records — accountable for their adoption, not just their publication.

Owns the team's roadmap, capacity allocation across work streams, and budget, including engagement of external consulting resources.

Translates and enforces the Data & AI architecture strategy set by the Global Director, and informs how it evolves.

Accountabilities Architecture Set  and enforce the standards for what is built on Databricks as the target architecture, what remains on Synapse for now, and what is retired — and on what evidence.

Decide how data products are aligned: source-aligned versus domain-aligned versus consumer-aligned, where ownership and stewardship sit, and where a conformed enterprise model (CDM/RDM) serves better than distributed ownership.

Review technical designs from solution architects and lead engineers against platform standards; give feedback that changes the design, not just documents it.

Define and evolve reference architectures, solution patterns and data contracts so that quality is built in rather than inspected in.

Lead design sessions with architects, engineering and business stakeholders on complex or contested problems.

Oversee transitional architectures through to legacy decommission, maintaining business continuity and closing the parallel run.

AI architecture

Set and enforce architecture standards for agentic systems: orchestration, tool and data access boundaries, evaluation, guardrails and observability.

Set and enforce architecture standards for ML systems: feature reuse, training and serving topology, model lifecycle, and monitoring for drift.

Approve AI solution designs with enough depth to arbitrate them on the technical merits, and in line with AI policy and applicable regulation.

Governance and regulation

Embed privacy-by-design and personal data handling requirements into platform patterns, particularly across commerce and omni-channel.

Maintain computational governance: data quality frameworks, contracts and lineage as platform capability rather than project effort.

Team leadership

Line management for four architects: coaching, performance, career development, hiring.

Establish ways of working — review process,…