The Data Architect owns the technical foundation of a new data-intensive benchmarking and analytics capability embedded in Onit's enterprise legal operations platform. This is a hands-on, engineering-focused architecture role at the start of a multi-phase programme, and the work is front-loaded: within the first quarter, the Data Architect will select the data platform, design the canonical data model that several product surfaces depend on, define the service contracts, and set the performance and multi-tenant data-isolation guarantees the team builds against. Working closely with the Lead Engineer, Lead Designer, Product Management, and Data Engineering, this role stays in the code, the query plans, and the review conversations rather than handing designs over a wall.
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.
Skills Required
- Typically 10+ years of software engineering experience, including substantial architect, principal, or staff-level experience owning system-level decisions.
- Experience designing data-intensive applications where query performance over large datasets is central.
- Experience evaluating and selecting data platforms for large-scale analytical workloads using documented cost and performance analysis.
- Strong SQL and relational data modeling skills.
- Practical experience with analytical or columnar data stores and understanding of when each is appropriate.
- Experience designing canonical data models fed by multiple source systems and consumed by multiple product surfaces.
- Experience designing and operating multi-tenant SaaS systems with structurally enforced data isolation.
- Hands-on performance engineering experience, including query profiling, latency-budget decomposition, and percentile-based measurement.
- Ability to document and defend architecture decisions and trade-offs to technical and non-technical stakeholders.
- Working proficiency with AI tools such as Claude or GitHub Copilot, including critical evaluation of generated output.
- API design experience with a contract-first mindset.
- AWS cloud platform experience, including infrastructure as code.
- Experience retrofitting analytics or reporting capabilities into an existing transactional product.
- Experience working with incomplete or inconsistent source data while maintaining trustworthy systems.
- Background in enterprise B2B SaaS or legal technology.
- Experience with data anonymization or aggregation where privacy guarantees matter.
What We Do
Onit is a global leader of enterprise software and artificial intelligence platforms and products for legal, compliance, sales, IT, HR and finance departments. Our software transforms best practices into smarter workflows, better processes and operational efficiencies. With a focus on enterprise legal management, matter management, legal spend management, contract lifecycle management and legal holds, we operate worldwide and help global companies and billion-dollar legal departments bridge the gap between systems of record and systems of engagement. Onit is the only company in our space with two platforms: Our leading no-code business process automation platform, Apptitude, and our business intelligence platform, Precedent. Apptitude allows customers to create, modify and deploy new software products and custom workflows. Onit’s legal AI platform, Precedent, enables our software products to read, write, and reason like a lawyer. Combined, the two platforms enable customers to digitally transform legal operations by automating processes, reducing costs and maximizing productivity with industry-leading cloud-based software.
