We’re hiring the single owner of the systems that hold our customer data, spanning Sales, Marketing, Customer Success, Support, and Finance and Accounting. Today that ownership is shared: several teams, plus an external development partner, each hold a piece. Everyone involved is capable, but split ownership means definitions drift between platforms, fields get added by ticket, and the same question can return different answers depending on which system you ask it in. This role consolidates all of it under one accountable owner.

The destination is a hub-and-spoke architecture: Salesforce as the system of record at the center, our GTM, post-sale, support, and billing platforms integrated as spokes with clearly owned field mappings, and a central data lake as the analytics layer so reporting no longer depends on which system you happen to ask. The goal is one customer record that holds from first touch through renewal, support, and invoice.

AI is central to how this role operates, not an add-on to it. You’ll use LLM tooling as leverage to cover a surface area that would otherwise take a team: reconciling data across systems, classifying and matching records, drafting documentation, and investigating discrepancies. You’ll also build AI into how the business runs, from account research and outreach personalization to signal extraction and scoring. And you’ll make our data usable by AI in the first place, since governed, well-defined data is the prerequisite for anything we automate on top of it.

This role reports to the CFO by design. Data governance is foundational here rather than a byproduct: the definitions behind our customer, funnel, and revenue numbers need a single accountable owner, held to the same standard as the numbers Finance reports. It is also hands-on. You’ll write the SOQL, build the fields and dashboards, make the data-model calls, and own the request queue end to end, rather than handing requirements to someone else and waiting.

Core responsibilities

Data governance & reporting architecture

Own the definitions behind our customer and funnel metrics, and reconcile them across Salesforce and every platform feeding it: sales engagement, enrichment, customer success, support, billing
Maintain the definitions of record: a documented data dictionary, change control on the object model, and clear ownership of every field that feeds a reported number
Own data hygiene as a standing discipline: deduplication of accounts and contacts, matching and merge rules, validation rules, and required-field enforcement so records enter clean instead of getting cleaned later
Diagnose and fix semantic mismatches between systems, including picklists collapsing into booleans, activity records that can’t be segmented by account attributes, and duplicate customer records
Build the reporting layer that lets Sales, Marketing, Finance, CS, and Support leadership open the same report and reach the same conclusion, including exec-level views by vertical
Unify the customer record across acquisition, retention, support, and billing so lifecycle and revenue questions can actually be answered
Apply LLM tooling to the grind of governance work: reconciling values across systems, surfacing duplicate and mismatch candidates, and keeping documentation current

Platform ownership & architecture

Own the Salesforce object model as a designed system rather than an accumulation of requests: fields, picklists, cross-object formulas, record structure, account hierarchy
Drive the hub-and-spoke buildout and the move toward a central data lake, sequencing integration work so each spoke lands with owned definitions rather than another source of drift
Serve as the single point of contact for inbound requests across Sales, Marketing, CS, Support, and Finance: triage, prioritize, and decide what gets built in-house versus routed to our external development partner
Make the master-data calls that outside vendors can’t, such as what constitutes a customer, how accounts map across systems, and what "active" means

Routing & automation reliability

Own lead and account routing end to end, and get automation accuracy to 100% with monitoring that catches drift before a rep does
Instrument the funnel to show where deals stall and why

AI-assisted systems & GTM automation

Build and maintain ICP scoring, intent signal pipelines, and account prioritization logic that feed outbound
Scale account research and outreach personalization using LLM-assisted workflows that are measurable and repeatable, not one-off prompts

What we’re looking for

5+ years in Business Systems, RevOps, Sales Ops, Marketing Ops, or a comparable technical operations function
Deep Salesforce data fluency. You know the object model cold, write SOQL, build cross-object formula fields and reports without a tutorial, and understand how CRM data has to be structured to be trustworthy downstream
Cross-system diagnostic instinct. You’ve traced a reporting discrepancy to its root by inspecting the actual shape of the data, not by trusting a field name
Integration experience. You’ve owned a sync between Salesforce and at least one adjacent platform, including the field mapping and the entity-resolution decisions that come with it
Warehouse or lake exposure. You’ve moved CRM, GTM, and post-sale data into a central analytics environment (Snowflake, Databricks, BigQuery, or similar) and modeled it for reporting
AI fluency. You already work this way: LLMs in production for classification, extraction, summarization, and prompt chaining, and AI tooling woven into your own workflow rather than tried once
Governance discipline. You document definitions before you build, version your changes, enforce hygiene at the point of entry rather than by periodic cleanup, and hold a standard when it would be faster not to
Ownership under ambiguity. You turn open-ended business questions into working systems with minimal specification. Consulting, agency, or early-stage backgrounds fit well here
Collaboration and communication. You partner well across teams you don’t manage, translate between technical constraints and plain business language, and write decisions down so other people can follow and build on them
Stakeholder range. Comfortable serving Sales, Marketing, Finance and Accounting, CS, and Support at once, holding the line when a request conflicts with the data model, and doing it without spending the relationship

Strong plus: Python (pandas, transformation pipelines, scoring models), workflow orchestration (n8n, Zapier, or custom) Apex-level development stays with our external partner. You’ll direct that work, not write it.

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