Principal Systems & Data Analyst

The opportunity

Our Growth Marketing team runs on a modern stack:
Hub Spot, Salesforce, Qualified, 6sense, Outreach, Amplitude, and Looker, and we're looking for a senior, hands-on individual contributor, a Principal Systems & Data Analyst, to become the person who makes that stack trustworthy. You'll own how we measure and attribute pipeline, set the standards for data health and hygiene across our systems, and define how we manage customer and account data.

This is not a reporting-only analyst role. It sits upstream of analytics, owning the data foundations, system logic, and attribution design that make reporting trustworthy. This is a foundational role in a growth marketing function that delivers a substantial quarterly pipeline, and you'll have real influence over how that pipeline is measured, trusted, and reported.

You'll join our Systems & Data team within Lifecycle & Marketing Operations, working alongside our Marketing Systems Architect, who owns stack architecture and integrations, and our Marketing Operations team, who manage day-to-day platform administration. You'll also partner closely with our SDR Operations and the entire Growth and Brand Marketing teams to ensure data standards hold across the entire funnel, not just marketing.

• Design and implement a new attribution model or tool for our growth-marketing funnel, then build and maintain pipeline and attribution reporting in Looker and Amplitude.
• Define field standards, deduplication rules, and data quality SLAs across Hub Spot and Salesforce, and partner with our operations team to embed them in day-to-day practice.
• Map and improve end-to-end data flows across Hub Spot, Salesforce, and adjacent systems, identifying sync gaps, source-of-truth conflicts, and reporting risks before they affect pipeline measurement.
• Support regional and growth-marketing teams with practical attribution and performance questions, including campaign and event measurement, while building clear definitions the broader team can use without tribal knowledge.
• Own source-of-truth definitions for customer and account data, partnering with customer-facing systems where growth and customer data intersect.
• Partner with our SDR Operations team so data health, enrichment, and reporting stay consistent across the full funnel.
• Partner with our Marketing Systems Architect on integration and sync design so the data flowing through our systems supports clean, trustworthy reporting.
• Support our Lifecycle Marketing team with segmentation and performance reporting needs.
• Document data definitions, standards, and reporting logic so the team scales without relying on tribal knowledge.

• 8+ years of experience in marketing or revenue analytics, attribution modeling, or data analysis in a B2B SaaS environment, with a track record of owning complex outcomes independently at a senior level.
• Hands-on experience with Hub Spot and Salesforce data models.
• Experience evaluating and implementing attribution tools or models.
• Experience translating marketing and revenue measurement needs into requirements for centralized Analytics, data engineering, or business intelligence teams.
• Working knowledge of modern analytics foundations such as data warehousing, dbt, LookML, and BI governance; deep hands-on ownership of the shared Analytics stack is not required.
• Strong SQL and data manipulation skills; experience with Looker and/or Amplitude is a plus.
• Strong experience using AI tools to analyze data quality; familiarity using AI tools inside tech stack (6sense, Qualified, Outreach)
• Experience using LLMs for natural language reporting, setting up self-serve analytics
• Experience applying LLMs or AI tools to natural-language reporting, data-quality workflows, or self-service analytics, with an understanding of the importance of centralized definitions, access controls, and reporting governance.
• A track record of building data quality and hygiene standards and driving the adoption of them.
• Strong communication skills, with the ability to translate data findings for non-technical stakeholders.
• Comfort partnering across operations, SDR, and lifecycle teams.

• Experience with 6sense, Qualified, or Outreach data models.
• Experience operating in a fast-scaling B2B SaaS revenue engine.
• Exposure to AI-assisted reporting or analytics tooling.