Data Architect

Key Responsibilities

• Architecture Ownership: Own the end-to-end architecture for a data-intensive analytics capability embedded in an existing enterprise product.

• Data Platform Selection: Evaluate and select the data platform for large-scale analytical queries, with a documented cost and performance basis for the decision.

• Canonical Data Model: Design a canonical data model that multiple source systems feed and multiple product surfaces consume, ensuring figures reconcile consistently across every surface.

• Service Contracts & APIs: Define and publish service contracts and API specifications using a contract-first approach.

• Non-Functional Requirements: Set and defend latency targets, refresh cadence, and availability requirements, and make them measurable rather than aspirational.

• Multi-Tenant Data Isolation: Design tenant data isolation so that it is enforced structurally, not by convention.

• Architecture Decisions & Reviews: Write architecture decision records that explain trade-offs honestly, including what would change the decision, and review designs and code across the team.

• Cross-Functional Translation: Translate technical constraints into terms Product and Design can act on, and translate their requirements back into architecture.

Required Skills

• Typically 10+ years in software engineering, including substantial time in an architect, principal, or staff-level role owning system-level decisions.

• Demonstrable experience designing data-intensive applications: systems where query performance over large datasets is the central problem.

• Experience evaluating and selecting data platforms for large-scale analytical workloads, with a documented cost and performance basis for the decision.

• Strong SQL and relational data modelling; practical experience with analytical or columnar data stores and a clear view of when each is appropriate.

• Experience designing canonical data models that multiple source systems feed and multiple product surfaces consume, with figures that reconcile consistently.

• Experience designing and operating multi-tenant SaaS systems, including data isolation enforced structurally rather than by convention.

• Hands-on performance engineering: able to profile a slow query, decompose a latency budget, and define what to measure and at which percentile.

• Writes decisions down clearly (e.g., architecture decision records that explain trade-offs honestly) and can defend them to both engineers and non-engineers.

• Working proficiency with AI tools (e.g., Claude, GitHub Copilot) to accelerate design exploration, query analysis, and documentation, with the judgment to critically evaluate AI-generated output.

Preferred Qualifications

• API design experience with a contract-first mindset.

• Cloud platform experience (AWS), including infrastructure as code.

• Experience retrofitting analytics or reporting capability into an existing transactional product.

• Experience working with incomplete or inconsistent source data, and designing systems that stay trustworthy despite it.

• Background in enterprise B2B SaaS or the legal technology domain.

• Experience with data anonymisation or aggregation where privacy guarantees matter.