RevOps Analyst

Overview

You're the person who makes sure leadership knows what's actually happening in the revenue engine. You build executive dashboards, own funnel reporting from MQL to closed-won, and dig into data when someone asks "why did bookings drop 15% last month?" You work closely with sales ops, marketing ops, and revenue leadership - translating business questions into data queries and findings into actionable insights.

Role Snapshot

Company Context

Stage: Series C (raised $77M total, $276M valuation as of Nov 2021)

Size: 221 employees

Growth: Actively hiring across GTM. Recent $33M Series C (Oct 2023) suggests scaling mode. Product has strong adoption (4.6/5 on G2 from 245+ reviews).

Market Position: Growing player in device intelligence/fraud prevention. Competing against Sift, SEON, Signifyd, and others. Category is heating up as fraud and bot detection become critical for e-commerce and SaaS companies.

GTM Reality

What You're Supporting:

• Sales team selling device intelligence platform to enterprise software companies and e-commerce brands
• Likely mix of inbound (product has PLG elements - open source FingerprintJS) and outbound enterprise motion
• Marketing driving demand gen, SDRs/BDRs qualifying, AEs closing consultative deals
• Probably tracking metrics like: MQL to SQL conversion, meeting-to-opp rate, opp-to-close rate, sales cycle length, win rate by segment

Data Sources You'll Manage:

• Salesforce (likely CRM of record)
• HubSpot (marketing automation, possibly also CRM)
• Product usage data (for PLG motion)
• BI tool (Sigma, Looker, or Tableau)
• Spreadsheets that someone in sales built 2 years ago that everyone still relies on

What You'll Actually Do

Time Breakdown

Dashboard Building/Maintenance (35%) | Ad-hoc Analysis (30%) | Data Quality/Ops (20%) | Meetings (15%)

Key Activities

• Executive Dashboard Maintenance: You own the weekly/monthly revenue review decks. Pulling pipeline snapshots, forecast vs actuals, conversion rates by stage, win/loss analysis. When numbers look weird, you're the one who digs in to figure out if it's real or a data issue.

• Funnel Analysis: Someone asks "why are we generating more MQLs but booking fewer meetings?" You pull the data, segment by source/persona/region, and figure out if it's lead quality, SDR capacity, or something else. You write up findings and present recommendations.

• Data Integrity Work: Salesforce is messy. Duplicate records, stages that don't match the actual sales process, opportunities without close dates. You spend time cleaning data, building validation rules, and training people to enter things correctly (they won't, but you try).

• Building New Reports: RevOps Director needs to see rep productivity metrics. Marketing wants to understand which campaigns drive pipeline. You scope requirements, write SQL queries, build the dashboard, and iterate based on feedback. Some requests are one-time, others become recurring reports you maintain forever.

The Honest Reality

What's Hard

• Data is Always Messy: No matter how many Salesforce validation rules you build, reps will find creative ways to enter garbage data. You'll spend more time on data quality than you'd like.

• Everyone Wants Different Numbers: Sales wants to see pipeline one way, marketing another way, finance a third way. You're constantly reconciling different views of "truth" and explaining why the dashboard shows different numbers than someone's spreadsheet.

• Ad-hoc Requests Eat Your Time: You block off Friday to build that new cohort analysis, but then three "quick questions" come in that each take 2 hours to answer properly. Prioritization is constant.

• You're Only as Good as Your Data: If Salesforce data quality is poor, your insights are limited. You're dependent on others (sales, marketing) actually updating records correctly.

What Success Looks Like

• Leadership makes GTM decisions based on your dashboards and analysis (not gut feel or random spreadsheets)
• You reduce the number of "can you pull this for me" Slack requests by building self-service reports people actually use
• You catch data quality issues before they affect forecasting or comp calculations
• When pipeline drops or conversion rates change, you're the first to spot it and explain why

Who You're Working With

Direct Stakeholders:

• VP/Director of Revenue Operations (likely your manager)
• CRO or VP Sales (consumes your executive dashboards)
• Sales leaders (need rep performance metrics, territory planning data)
• Marketing leaders (want to prove marketing's impact on pipeline)
• Finance (need clean data for revenue recognition and forecasting)

What They Care About:

• Sales Leadership: Pipeline coverage, rep productivity, forecast accuracy, win rates
• Marketing: MQL to SQL conversion, campaign ROI, lead quality by source
• Finance: Clean data for revenue forecasting and commission calculations
• RevOps Leadership: Systems working together, scalable processes, accurate reporting

Requirements

• 2-4 years experience in SaaS revenue operations, sales operations, or GTM analytics
• Strong SQL skills - you're writing queries daily, not just using point-and-click tools
• Deep Salesforce experience - understanding objects, relationships, reporting limitations
• Experience with HubSpot or similar marketing automation platform
• Proficiency in at least one BI tool (Sigma, Looker, Tableau, or similar)
• Comfortable building executive-level dashboards and presenting findings
• Experience with GTM metrics (conversion rates, sales velocity, pipeline coverage, etc.)
• Ability to translate business questions into technical requirements and back into insights
• Bonus: Experience with Python/R for analysis, familiarity with data warehouses (Snowflake, BigQuery)