ELT platform connecting disparate business software into unified customer data
Hevo operates an ELT (extract-load-transform) data platform targeting mid-market companies struggling with siloed customer data across CRM, marketing, and financial systems. The stack reveals a mature data infrastructure play: Snowflake, BigQuery, Databricks, and Apache Iceberg on the warehouse side paired with Salesforce, HubSpot, and QuickBooks connectors on ingestion. Hiring velocity is accelerating with heavy senior/leadership weighting in sales and engineering, while projects split between scaling the product (data pipelines, observability) and scaling revenue (account expansion, upsell identification, QBR programs).
Hevo is a privately held data integration platform founded in 2017 and headquartered in San Francisco. The company helps organizations build a unified view of customer data by automating ETL/ELT workflows across multiple disconnected sources—sales platforms, advertising channels, marketing software, financial systems, and support tools. Hevo targets data and engineering teams at mid-market companies where fragmented data is blocking decision-making and revenue visibility. The platform writes transformed data into Snowflake, BigQuery, Redshift, or Databricks. With 201–500 employees and accelerating sales hiring, the company is in a growth phase focused on land-and-expand within existing accounts and improving net revenue retention.
Hevo uses Snowflake, BigQuery, and Databricks for warehousing; Apache Iceberg for data format; Salesforce and HubSpot for CRM/marketing connectors; Tableau and Looker for BI; Django and Python for backend; Jenkins and CircleCI for CI/CD; and Terraform/Ansible for infrastructure.
Hevo solves fragmented customer data across business software by automating data pipelines that combine CRM, marketing, financial, and support platforms into a unified warehouse—enabling companies to build 360-degree customer views and improve data-driven decision-making.
Hevo Data's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.