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.
• Strong data modelling: entity resolution, slowly changing dimensions, event and state modelling, semantic layer design.
• Experience designing Azure-native EDP topologies (workspaces, clusters, network, identity, cost controls).
• 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.