Revenue Operations Data & Systems Analyst

Overview

You're building and maintaining the data layer that powers HSI's revenue organization. This means cleaning CRM data, building BI dashboards, troubleshooting reporting issues, and helping the team understand pipeline health and funnel performance. You report to the Senior Director of Revenue Operations and work across sales, marketing, and customer success teams who need data to make decisions.

Role Snapshot

Company Context

Stage: Unknown (mature company - 779 employees suggests growth stage or established)

Size: 779 employees

Growth: Scaling GTM operations, investing in AI-enabled analytics infrastructure

Market Position: Unknown industry vertical, but size suggests established product-market fit

What You'll Actually Do

Time Breakdown

Data Analysis & Reporting (35%) | CRM/Systems Work (30%) | Cross-functional Requests (25%) | Meetings/Internal (10%)

Key Activities

• Building dashboards and reports: You're in Tableau, Power BI, or similar tools creating pipeline visibility dashboards, funnel analysis reports, and revenue forecasting views. Sales leaders will ask for custom cuts of data, and you'll spend time figuring out how to pull it correctly from Salesforce or whatever CRM they use.
• CRM data hygiene: A lot of your time goes to fixing bad data. Sales reps don't update opportunities correctly, fields are blank, stage progression doesn't make sense. You audit data quality, create rules, and chase people to fix their records so reporting is accurate.
• Ad-hoc analysis requests: Marketing wants to know conversion rates by campaign source. Sales leadership wants to understand why Q3 pipeline is down. Customer Success needs retention metrics by segment. You field these requests constantly and figure out how to answer them with the data you have.
• Systems administration: You're configuring fields in Salesforce, building automation rules, managing integrations between tools, and troubleshooting when data doesn't sync properly between systems. Not a full Salesforce admin, but you need to understand how the tech stack fits together.
• AI/analytics infrastructure projects: The posting mentions building "AI-enabled revenue intelligence" - this likely means working on data models, cleaning historical data for ML inputs, or implementing new analytics tools. Expect project work on top of day-to-day requests.

The Honest Reality

What's Hard

• Data is always messy: Sales reps don't follow processes. Fields are blank, deals are in wrong stages, contact info is duplicated. You'll spend significant time cleaning data before you can analyze it, and it's repetitive work.
• Everyone wants their request prioritized: Sales leaders, marketing, CS - they all need reports and they all think theirs is urgent. You're constantly triaging requests and managing expectations about timelines.
• You're dependent on others: If reps don't log activities or update Salesforce correctly, your data is garbage. You can build rules and send reminders, but you can't force compliance. This is frustrating when you're held accountable for accurate reporting.
• Hybrid requirement: The posting emphasizes in-person collaboration. If you're used to full remote work, this is a change. You'll need to be in the Frisco office regularly (exact cadence unclear, but "strong emphasis" suggests 3-4 days/week).
• Ambiguity around AI projects: "Building AI-enabled revenue intelligence" sounds interesting but is vague. This could mean implementing vendor tools, doing actual data science work, or just creating predictive dashboards. The scope isn't clear, which means expectations might shift.

What Success Looks Like

• Revenue leadership trusts your reports and uses them for actual decisions (not just checking boxes)
• Data quality improves - fewer blank fields, more accurate stage progression, cleaner pipeline snapshots
• You deliver analysis requests within agreed timelines and the insights actually drive action
• Systems run smoothly - integrations don't break, dashboards refresh on schedule, automation works
• You ship AI/analytics infrastructure projects that improve forecast accuracy or pipeline visibility

Who You're Working With

Internal Stakeholders:

• Revenue Operations Director (your manager) - expects data accuracy, project delivery, and proactive insights
• Sales leadership - want pipeline visibility, forecast accuracy, performance metrics by rep/region
• Marketing - need funnel conversion metrics, campaign attribution, lead quality analysis
• Customer Success - want retention data, expansion pipeline visibility, health score metrics
• Sales reps - you're asking them to fix their data, and they see it as admin work

What They Care About:

• Can they trust the data to make decisions?
• Can you deliver requests quickly without needing tons of hand-holding?
• Do you understand the business context or just run SQL queries?
• Can you explain technical findings to non-technical people?

Requirements

• 1-3 years in Revenue Operations, Sales Operations, or revenue analytics roles
• Hands-on experience with CRM systems (Salesforce most likely) - pulling reports, understanding data model, basic admin tasks
• BI/analytics tool experience (Tableau, Power BI, Looker, etc.) - building dashboards and visualizations
• Comfortable with data analysis - Excel/Google Sheets fluency at minimum, SQL is a major plus
• Understanding of B2B SaaS metrics (pipeline, conversion rates, sales cycle, ACV, etc.)
• Willing to work hybrid in Frisco/Dallas office with regular in-person presence
• Can translate business questions into data analysis and explain findings clearly to non-technical people
• Self-directed enough to manage multiple competing requests and prioritize effectively