Job Description
We’re looking for an experienced RevOps / Data Integration consultant to help us connect, clean up, and analyze data across our go-to-market and customer success tech stack.
Our tools include:
HubSpot (CRM, Marketing, Service, Customer Success / Health Scores)
Survicate
PandaDoc
Google Analytics
Apollo
Mailgun
YouTube
Future data warehouse and analytics layer
The goal is to reliably capture historical data, avoid overwriting key signals, and roll everything up into usable customer, revenue, and health insights for leadership.
This is not just “connect the API and walk away.” We need help with data modeling, best-practice architecture, and analytics readiness.
What You’ll Do:
Assist with designing and implementing integrations between HubSpot and our go-to-market tools
Advise on data modeling, such as properties versus events versus custom objects
Ensure historical survey and engagement data is preserved
Help define inputs to HubSpot Customer Health Scores
Recommend and or implement a data warehouse and analytics tool, with a preference for low-code solutions
Validate data quality, consistency, and reporting accuracy
Document the architecture so it is maintainable long-term
What We’re Looking For:
Proven experience with HubSpot RevOps and CRM architecture
Hands-on integration experience using APIs, native connectors, or integration platforms
Strong understanding of event data versus point-in-time properties
Experience with data warehouses such as BigQuery, Snowflake, or Redshift
Familiarity with analytics tools like Looker, Metabase, Power BI, Tableau, or Hex
Ability to explain tradeoffs clearly to non-technical stakeholders
Comfortable working hourly and scoping work incrementally
Nice to Have:
Experience integrating Survicate or other survey tools
Customer Success and Health Score modeling experience
Background in B2B SaaS or subscription businesses
Experience implementing ELT tools such as Fivetran, Airbyte, Segment, or RudderStack
Engagement Details:
Contract and hourly engagement
Initial scope focused on integration and architecture design
Ongoing optimization is likely
Expected data volume 35-100 terabytes over five years
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Apply Now