Own the Salesforce object model, record types, account hierarchy and relationships so the data structure matches how the business operates across our four product lines
Resolve the structural issues blocking clean reporting, including account hierarchy, duplicate records and field level data integrity, and hold them under ongoing governance
Productionise data work that currently lives outside the platform, including deduplication and partner and account matching, into governed, repeatable processes inside Salesforce
Own the integration layer between Salesforce, DealHub and other revenue systems, designing integrations to be maintainable and observable rather than brittle
Diagnose and fix the quote to cash issues that break reporting and slow deals, including pricing, product configuration and revenue fields presenting incorrectly
Build the data layer, report types and dashboards that give RevOps, Finance and the leadership team a single source of truth, reconciled to the finance validated figures the board uses
Remove the manual workarounds RevOps currently runs to patch around platform gaps
Own the development lifecycle across sandboxes, version control, deployment, testing and release management, and set the technical standards that keep the platform clean as it scales
Triage and resolve platform issues, working with the Revenue Operations Administrator on the split between declarative and engineered solutions
Partner with the RevOps Lead on the platform roadmap and translate commercial needs into technical design
Requirements
5+ years Salesforce development experience: Apex, Lightning Web Components, SOQL, Flow and the declarative toolset, with the judgement to know when to use each
Proven data modelling and platform architecture experience, ideally in a multi product B2B SaaS environment
Hands on integration experience using Salesforce APIs and middleware, with a track record of fixing or replacing fragile integrations
Experience building reporting and dashboards that finance and leadership rely on, and a clear understanding of how data quality drives reporting accuracy
Disciplined development practice across source control, sandboxes, testing and managed deployment (for example Gearset or similar)
Excellent communication skills, able to explain technical decisions and trade offs to non technical stakeholders at all levels
Confident using AI tools to improve productivity, problem solving, documentation, process design, testing and operational efficiency. Able to identify where AI can add value, apply it responsibly, and use sound judgement around accuracy, data security and appropriate business use.
Benefits
Flexible working
we ask that you work during core hours (10-4) to help with collaboration, but outside of that you can work when suits you
10 Time to Learn days
Birthdays off
Opportunity to develop within a fast-growing tech business with an ambitious year-on-year growth trajectory