Data Architect

We are hiring a Data Architect to join an Intellias delivery team on a large-scale enterprise data platform migration programme for a financial services client. This is a hands-on architect role. You will co-own the pattern library with the client’s architecture team, write reference implementations, and unblock engineering decisions across the programme. Project Overview: Our client is an independent, active global asset manager with over R3 trillion in assets under management. They are executing a firm-wide data strategy to govern, manage and engineer data as a product across more than 70 business-owned sub-domains. As part of this, they are migrating to Databricks as the foundational layer of their Enterprise Data Platform, adopting a lakehouse architecture built on open formats, declarative pipelines and Unity Catalog. Requirements: 10+ years of data platform architecture experience, with several years on Databricks in production. Deep hands-on knowledge of Delta Lake, Unity Catalog, Lakeflow Declarative Pipelines, Spark, Photon and Databricks Asset Bundles. Experience implementing enterprise data catalogues (Collibra, Purview, Alation, AWS DataZone or similar) integrated with a technical catalogue. Comfortable writing reference code, reviewing PRs and pairing with engineers. Fluent working English. Nice to have Active Databricks certifications Prior exposure to investment management platforms, asset management operations data, market data feeds from major providers CDMP DAMA or TOGAF certification. Experience applying agentic engineering tooling to platform work, including MCP-connected Databricks or cloud servers. Responsibilities: Own the Lakehouse architecture, Unity Catalog design and medallion standards that every domain team builds against. Author and maintain Architecture Decision Records for the platform. Design integration patterns for ingestion, processing and serving, and codify them as reusable reference implementations. Review domain designs and contribute to code reviews. Co-own the reference pattern library and evolve it wave over wave. Design FinOps guardrails and observability across the platform. Contribute to agent rules and skill definitions so architectural standards are enforced by generation rather than documentation. Why this position: Own the architecture of a large-scale enterprise data platform migration from the ground up — reference patterns, Unity Catalog design and medallion standards that every domain team builds against. You'll work at the leading edge of the Databricks ecosystem on a high-stakes lakehouse build, applying agentic engineering tooling to enforce standards through generation rather than documentation, and shaping the platform's technical foundations alongside a parallel data governance workstream. #J-18808-Ljbffr