Advisory Data Architect

About Unity Advisory

Unity Advisory is a modern advisory business built for today's CFO, with connected solutions across finance, deals and tax. Focussed on client outcomes, seasoned experts lead every engagement, in an operating model powered by AI and free from audit conflict.

The Role

We are looking for an experienced Advisory Data Architect to own data design across our advisory engagements. This is a platform and design-authority role with a hands-on edge, combining finance-focused business understanding with modern data architecture, platforms and governance. You will define how data - across a client’s business - is structured, governed, and served so that AI, analytics, and management reporting are reliable and scalable. As a Senior Manager, you will lead architecture decisions, guide engineers, shape client data strategy, architecture, governance, and be accountable for the coherence and quality of the data estate you design.

This is a client-facing role within our AI Advisory team, setting the data architecture that our engagements — and our clients' AI ambitions — are built on.

Key Responsibilities

• Define target-state data architectures for clients — models, storage, pipelines, and access patterns — balancing rigour with delivery realism.

• Establish data modelling standards and curated domain layers across the a variety of systems (e.g. ERP, CRM, Manufacturing) and data sources, with end-to-end lineage and provenance sufficient for audit and controls.

• Map and integrate finance source systems (ERP, EPM, sub-ledgers, and consolidation tools) into governed, analytics-ready models.

• Design the finance data foundations for applied AI/ML: governed retrieval sources for RAG, feature stores, and the architecture that keeps AI systems fed with trustworthy, reconciled finance data.

• Set patterns for secure, compliant finance data platforms — access control, data sensitivity, segregation of duties, isolation, and alignment to standards such as ISO 27001.

• Provide architectural direction for cloud data platforms, infrastructure as code, CI/CD, and observability, ensuring designs are cost-aware and operable.

• Define the data lineage and controls that support responsible production AI — monitoring, confidence scoring, and human-in-the-loop review.

• Translate ambiguous business and client problems into clear architectural decisions and scoped roadmaps under delivery pressure.

• Own key technical trade-offs and communicate them clearly to engineers, product stakeholders, and senior client sponsors.

• Mentor data engineers, raise the technical bar across the team, and contribute reusable patterns, reference architectures, and accelerators.

What We're Looking For

Essential

• Significant experience designing and delivering data architectures for production systems, with evidence that your designs have shipped and run - not remained on paper.

• Deep expertise in data modelling, warehouse/lakehouse design, and data governance.

• Hands-on background in SQL and Python, and fluency with at least one major cloud provider (AWS or Azure) and modern data platforms (e.g. Snowflake, Databricks).

• System-level judgement on how data architecture shapes AI outcomes: designing governed sources for RAG, structuring data for retrieval and orchestration, and deciding where structured outputs and tool use fit.

• Ability to set standards and lead engineers while remaining close to implementation.

• Strong stakeholder skills, including engaging senior client sponsors and explaining architectural trade-offs clearly.

Strong Preference

• Experience architecting the data layer behind AI or analytics products in production.

• Informed views on the trade-offs between fine-tuning, RAG, and long-context approaches, and how each changes data architecture requirements, including context window economics and prompt caching.

• Familiarity with infrastructure as code, CI/CD, and observability for data platforms.

• Awareness of MCP and tool-orchestration concepts and their implications for composable, data-driven AI systems.

• Fluent use of AI-assisted development tools (e.g. Claude Code, Cursor), with a clear view of where they help and where human design judgement must lead.

• Security and compliance experience (e.g. ISO 27001 alignment, access control design).

• Consulting or advisory background, owning problems end-to-end rather than a single workstream.

Nice to Have

• Evidence of self-directed building — side projects, internal tools, or startups.

• Exposure to finance data, PE/M&A, or portfolio-company environments.

• Relevant certifications (e.g. AWS/Azure architect-level credentials).

Additional Information

We are committed to an inclusive and accessible recruitment process. Please let us know if you need any reasonable adjustments or support when applying or arranging your interview.

We do not accept unsolicited CVs from third-party agencies.