Finance Data Architect

About Unity Advisory Unity Advisory is a pragmatic, outcome-focused advisory firm that bridges strategy and execution, supporting CFOs and finance leaders through transformation, transactions, and scaling journeys. 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. The Role We are looking for an experienced Finance Data Architect to own finance data design across our AI Advisory engagements. This is a platform and design-authority role with a hands-on edge, combining deep finance domain knowledge with modern data architecture. You will define how finance data — across the general ledger, sub-ledgers, close, consolidation, reporting, FP&A, and valuation — is structured, governed, and served so that AI, analytics, and management reporting are reliable and scalable, and you will stay close enough to implementation to make your designs real. As a Senior Manager, you will lead architecture decisions, guide engineers, shape client finance data strategy, and be accountable for the coherence and quality of the finance data estate you design. Key Responsibilities - Define target-state finance data architectures for clients — models, storage, pipelines, and access patterns — balancing rigour with delivery realism. - Establish finance data modelling standards and curated domain layers across the general ledger, sub-ledgers, close and consolidation, management and statutory reporting, FP&A, and valuation, with end-to-end lineage and provenance sufficient for audit and controls. - Design chart-of-accounts, dimensional, and master-data structures that support consistent, reconcilable reporting across entities and source systems. - 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. 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 At Unity Advisory, we are committed to providing an inclusive and accessible recruitment process. In line with the Equality Act 2010, we will accommodate any suitable candidate requiring assistance to attend or conduct an interview. If you need any adjustments or support, please let us know when scheduling your interview or in your application cover letter. We are dedicated to ensuring everyone has an equal opportunity to succeed and are here to support you throughout the process. PLEASE NOTE: We do not accept unsolicited CVs from third-party agencies.