Revenue Technology - Data Strategy & Operations Lead

<p>Mercury is redefining *banking for ambitious companies and behind every great financial platform is a data system that people can actually trust.</p> <p>As Mercury scales, our revenue systems generate an enormous amount of information: signals from remote and in-person meetings, automation tools, product usage, lifecycle events, and analytics pipelines. Turning that activity into clear, reliable intelligence — without brittle pipelines or constant rework — is critical to how we grow.</p> <p>We’re looking for a Data Strategy &amp; Operations leader to own the data foundations that power revenue execution. This role ensures that revenue data is reliable, interpretable, scalable, and usable as the business evolves and that teams can act on what they see with confidence.</p> <p>In this role, you will report to the Head of Platforms &amp; Infrastructure and play a central role in shaping how Mercury models, governs, and operationalizes GTM data. You’ll partner closely with Data Engineering, Data Science, Solution Architecture, Platform Engineering. etc.</p> <p><em>*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.</em></p> <h3>Here are some things you’ll do on the job:</h3> <ul> <li>Own the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)</li> <li>Serve as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows</li> <li>Design and evolve core GTM data models across Salesforce, ETL, and analytics layers</li> <li>Partner with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers</li> <li>Partner with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates</li> <li>Own clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity</li> <li>Define and uphold data quality, freshness, consistency, and documentation standards for revenue platforms</li> <li>Monitor and improve pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations</li> <li>Identify opportunities to automate manual or error-prone data workflows and reduce operational overhead</li> <li>Act as a data thought partner to Platforms &amp; Infrastructure, Revenue Operations, Analytics, and Security — advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives</li> </ul> <h3>