Sales Operations Manager

Overview

You're the first Sales Operations hire at ClariLayer, a metric lifecycle management platform that's essentially a 1-person company right now. You'll build the entire GTM stack and processes from the ground up—CRM configuration, CPQ/billing setup, data models, forecasting logic. The founder (ex-Databricks, ex-Cloudflare) needs someone to turn early sales motions into repeatable systems.

Role Snapshot

Company Context

Stage: Pre-seed / Stealth (1 employee per LinkedIn)

Size: 1 employee (the founder)

Growth: Just starting to hire GTM—you'd be employee #2 or #3

Market Position: Category creation—metric governance/observability is emerging but not well-defined

GTM Reality

Current State: There is no GTM motion yet. That's what you're building.

What Needs to Happen:

• Define ICP and target personas (likely data engineering, analytics, BI teams)
• Choose and implement CRM (probably HubSpot or Salesforce)
• Build initial outbound playbook (messaging, sequences, territories)
• Set up basic CPQ and billing workflows
• Create pipeline stages, forecast models, reporting dashboards

Challenges:

• You're not joining a sales team—you're creating the foundation for one
• No existing deals to learn from, no historical data
• Founder is technical (ex-engineer at Databricks/Cloudflare), may need help translating product vision into GTM strategy

Competitive Landscape

Main Competitors: Likely competing against:

• dbt metrics layer
• Transform.co
• Lightdash
• Build vs buy (companies building homegrown metric governance)

How They Differentiate: Focused on metric lifecycle management (define → validate → release → observe), not just metrics as code

Common Objections:

• "Can't we just use dbt for this?"
• "We already have a data catalog"
• "Our data team can build this internally"

Win Themes: Governance + observability in one platform, prevents metric drift across BI tools and AI agents

What You'll Actually Do

Time Breakdown

Systems Setup (40%) | Process Design (30%) | Analysis/Reporting (20%) | Meetings (10%)

Key Activities

• CRM Architecture: Choose platform, configure objects (accounts, contacts, opps), set up automation, build views and reports. This is hands-on admin work.
• Data Modeling: Design how you'll track pipeline, forecast accuracy, conversion rates, rep activity. Build Looker/Metabase dashboards from scratch.
• Process Documentation: Write the sales playbook—qualification criteria, stage definitions, handoff points (when you hire SDRs/AEs). Lots of Notion/Confluence docs.
• Tool Evaluation: Research and implement CPQ, quoting, contract management, billing integration. Compare vendors, run demos, negotiate contracts.
• Sales Enablement Support: Once reps are hired, create pitch decks, battle cards, ROI calculators, objection handling guides.
• Weekly Sync with Founder: Review early deal progress, adjust strategy based on what you're learning from initial conversations.

The Honest Reality

What's Hard

• Extreme ambiguity: No one knows what works yet. You're making educated guesses with no validation.
• You're building for a future team: Right now it's just the founder doing sales. You're building systems for 5-10 reps who don't exist yet. Easy to over-engineer or under-build.
• Startup risk: This is a 1-person company. Funding situation is unknown. They may not make it past 12 months.
• Taiwan location: GTM motion will likely target US/EU companies, so time zone challenges for any prospect/customer interaction.
• Category creation is hard: Metric governance isn't a recognized budget line. Long education cycles, hard to generate inbound demand.

What Success Looks Like

• First 3 pilot customers using ClariLayer, clean data flowing into CRM
• Repeatable outbound motion documented (even if conversion rates are still TBD)
• CRM/CPQ/Billing stack operational, founder can quote and close deals without you
• Forecast model that gives founder confidence in pipeline health
• Ready to onboard first AE when funding allows

Who You're Selling To

Primary Buyers:

• VP of Data / Chief Data Officer
• Director of Analytics / BI
• Head of Data Engineering

What They Care About:

• Metrics defined inconsistently across teams (marketing says one thing, finance says another)
• Breaking changes in metric definitions causing reporting failures
• Can't trust metrics used in AI agents or embedded analytics
• Manual overhead maintaining semantic layers in dbt or LookML

Requirements

• 5+ years in Sales Operations or Revenue Operations (preferably in B2B SaaS)
• Deep hands-on experience with CRM admin (Salesforce or HubSpot), not just "power user"
• Understanding of enterprise sales motions—you've seen how deals flow from qualification to close
• Experience building GTM systems from early stage (Series A/B), not just optimizing mature processes
• Comfortable with ambiguity and making decisions with incomplete information
• Based in Taiwan or willing to relocate (founder is based there)
• Bonus: Background in data tooling, analytics, or BI (helps understand the buyer)
• Bonus: SQL skills for pulling your own reports, building data models