Solution & Data Architect: Databricks Champion
The Solution & Data Architect will provide end-to-end solution and data architecture leadership for a manufacturing client’s Operational Intelligence MVP. We’re looking for a true Databricks champion, someone who lives and breathes the platform and can show it.
The role will turn the client’s Order-to-Invoice processes and financial-control requirements into a practical Databricks solution, working across business stakeholders, platform teams and the engineering team.
This is a delivery-focused architecture role, not advisory-only. You’ll stay close to implementation, own design authority, resolve technical and data issues, and make sure the reusable patterns built for Client 1 carry across to Clients 2 and 3. You’ll need to be hands-on and able to contribute directly to development, troubleshooting and implementation where the delivery team needs it.
Key responsibilities
Business and solution architecture
· Understand the client’s end-to-end Order-to-Invoice processes and translate them into an implementable data and solution architecture.
· Work closely with BAs and teams across Finance, Client Services and technical SMEs to understand business rules, reconciliations, controls and expected outcomes.
· Design the overall Databricks-based Operational Intelligence solution across ingestion, transformation, data modelling, data quality, reconciliation and consumption.
· Keep clear traceability between business requirements, source data, technical design and delivered outputs.
· Set pragmatic MVP boundaries and challenge requirements or designs that add unnecessary complexity.
· Provide architectural leadership throughout delivery, not just upfront design.
Data architecture and modelling
· Define the Conformed Operational Intelligence data model connecting order, job, cost/charge, revenue and invoice concepts.
· Design Bronze, Silver and Gold structures and modelling patterns.
· Define business keys, relationships, transformations and reconciliation approaches across mixed operational and finance data.
· Work with business SMEs to turn invoice validation, revenue assurance and basic cost/revenue/margin requirements into robust data structures and processing rules.
· Make sure the architecture supports auditability and investigation of exceptions.
Databricks architecture
· Act as the Databricks champion, providing strong architectural leadership for the lakehouse implementation.
· Define patterns for ingestion, transformation, orchestration, storage, security and governance.
· Design and lead a reusable, metadata-driven ingestion framework for structured and file-based sources, enabling repeatable onboarding across multiple source systems and client data flows.
· Guide on Unity Catalog, environment structure, access/security patterns and CI/CD.
· Work effectively with the client’s Azure/platform specialists on infrastructure, networking, identity and connectivity decisions.
· Understand the infrastructure implications well enough to challenge designs and spot dependencies, without needing to be the hands-on Azure platform engineer.
· Guide engineering decisions on performance, scalability, supportability and cost.
Essential experience
· Strong, practical experience designing and delivering production solutions on Databricks. A genuine Databricks champion.
· Proven track record providing architecture leadership through implementation, working directly with engineering teams.
· Experience delivering Finance-led or financial-control data programmes, including reconciliation and operational-to-financial data flows.
· Strong data architecture and modelling experience across operational and financial datasets.
· Experience turning complex business rules and financial controls into implementable data solutions.
· Strong understanding of Databricks lakehouse patterns, Delta Lake, Unity Catalog, security/governance and CI/CD.
· Good working knowledge of Azure infrastructure around Databricks, particularly identity, networking, storage and connectivity.
· Strong stakeholder-management skills across Finance, business and technology audiences.
· Strong commercial awareness, including managing scope, spotting delivery implications and making pragmatic MVP trade-offs.
Desirable experience
· Designing or delivering metadata/configuration-driven ingestion frameworks.
· Invoice assurance, revenue assurance or financial reconciliation experience.
· Job/order costing or margin-reporting experience.
· Manufacturing, production, print/fulfilment, logistics or another process-driven operational environment.
· Integrating structured sources with file/document-based inputs.
· Databricks professional-level architecture or engineering certification.