HubSpot → Data Warehouse

Connection methods and marketing analytics tables

Sortment internal reference - onboarding playbook

This document is a definitive reference for every supported method of connecting HubSpot marketing data into a data warehouse, and for every table available in each method. It is structured for merchant onboarding - specifically to determine which tables Sortment can expect to find when it is granted read access to a merchant's data warehouse schema, and how to build accurate email campaign analytics from those tables.

Merchants may be running several data warehouses, including Snowflake, Amazon Redshift, Google BigQuery, AWS Athena, or Databricks. This document covers all common pipeline methods. Where a method or SQL syntax is specific to one warehouse platform, it is explicitly noted.

Each method section includes: (a) a description of how the pipeline works and what it requires, (b) a complete table reference for marketing-relevant tables, and (c) gotchas and caveats that affect query accuracy. The final sections cover the sent → opened → clicked → converted funnel pattern and a decision matrix for matching each merchant to the right method.

---

1. Connection methods at a glance

HubSpot data can reach a data warehouse through six distinct paths. The method determines what schema the data lands in, how fresh it is, and critically, what tables are available for marketing analytics.

Method	Provider	HubSpot Tier Req.	Latency	Data Lands In
Native Data Share (Snowflake only)	HubSpot (built-in)	Ops Hub Professional+	15 min (Live) / Daily	Shared DB (read-only)
Fivetran ETL	Fivetran	Any HubSpot tier	Configurable (15 min+)	Merchant's own schema
Airbyte ETL	Airbyte (open-source or Cloud)	Any HubSpot tier	Configurable	Merchant's own schema
Stitch (Qlik) ETL	Qlik/Stitch	Any HubSpot tier	Configurable	Merchant's own schema
Estuary Flow	Estuary	Any HubSpot tier	Near real-time	Merchant's own schema
Windsor.ai / Supermetrics	Windsor / Supermetrics	Any HubSpot tier	Daily typical	Merchant's own schema

The most common pattern in merchant stacks encountered during Sortment onboarding is Fivetran (managed ETL) followed by HubSpot's Native Data Share (Snowflake accounts only). Airbyte and Stitch are less common but follow the same logical data model and work with any warehouse destination.

---

2. Method A: HubSpot Native Snowflake Data Share

Snowflake-specific. This method uses Snowflake's Secure Data Sharing technology and is only available to merchants whose data warehouse is Snowflake. Merchants on Redshift, BigQuery, Athena, or Databricks must use one of the ETL-based methods (B–F) instead.

How it works

HubSpot acts as the Snowflake data provider. No data is physically copied - Snowflake's Secure Data Sharing grants the merchant's Snowflake account read-only access to a shared database that HubSpot maintains. The merchant sees the data in their Snowflake instance without any ETL infrastructure.

• Requires: Operations Hub Professional or Enterprise

• Latency: V2_LIVE schema refreshes every 15 minutes; V2_DAILY refreshes once per day

• Schema naming: HUB_{portalId}_DB.V2_LIVE.{TABLE_NAME} or .V2_DAILY.{TABLE_NAME}

• Read-only: the merchant cannot write back to this database

V2_LIVE and V2_DAILY contain the same tables. V2_LIVE is preferred for near-real-time queries. V2_DAILY is preferred for large batch analytics to avoid query cost on a rapidly updating dataset. Some views (association_definitions, owners, pipelines, pipeline_stages) are only updated daily even in V2_LIVE.

2.1 Email event tables

Email event data is sharded: each event type is its own table. You query them separately and join on OBJECTID (contact ID) and PROPERTY_HS_EMAIL_CAMPAIGN_ID.

Table Name (V2_DAILY / V2_LIVE)	Event Type	Key Columns
EVENTS_SENT_EMAIL_V2	Send event per contact	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_DELIVERED_EMAIL_V2	Confirmed delivery	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_OPENED_EMAIL_V2	Email open	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_CLICKED_LINK_IN_EMAIL_V2	Link click	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID, PROPERTY_HS_CLICK_ORIGINAL_URL
EVENTS_BOUNCED_EMAIL_V2	Hard or soft bounce	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID, PROPERTY_HS_BOUNCE_REASON
EVENTS_UNSUBSCRIBED_FROM_EMAIL_V2	Unsubscribe	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_MARKED_EMAIL_AS_SPAM_V2	Spam report	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_FORWARDED_EMAIL_V2	Email forward	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_SCHEDULED_EMAIL_V2	Scheduled for send	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_DEFERRED_EMAIL_V2	Send deferred (temp. failure)	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID
EVENTS_DROPPED_EMAIL_V2	Dropped before send	OBJECTID, OCCURREDAT, PROPERTY_HS_EMAIL_CAMPAIGN_ID

2.2 Object tables

Object tables hold current-state records for each HubSpot object. Properties are flattened as columns (PROPERTY_*).

Table Name	What It Contains	Key Columns
OBJECTS_CONTACTS	All CRM contacts	OBJECTID, PROPERTY_EMAIL, PROPERTY_FIRSTNAME, PROPERTY_LASTNAME, PROPERTY_HS_LEAD_STATUS
OBJECTS_CAMPAIGNS	Marketing campaign records	OBJECTID, PROPERTY_HS_NAME, PROPERTY_HS_GOAL, PROPERTY_HS_BUDGET_ITEMS_SUM_AMOUNT
OBJECTS_MARKETING_EMAILS	Email asset metadata	OBJECTID, PROPERTY_HS_NAME, PROPERTY_HS_SUBJECT, PROPERTY_HS_SEND_DATE, PROPERTY_HS_CAMPAIGN_ID
OBJECTS_DEALS	Deal pipeline records (conversion signal)	OBJECTID, PROPERTY_DEALNAME, PROPERTY_AMOUNT, PROPERTY_DEALSTAGE, PROPERTY_CLOSEDATE
OBJECTS_FORMS	Form submissions (alt. conversion signal)	OBJECTID, PROPERTY_HS_FORM_ID, PROPERTY_HS_NAME, PROPERTY_HS_CREATED_AT
OBJECTS_COMPANIES	Company / account records	OBJECTID, PROPERTY_NAME, PROPERTY_DOMAIN, PROPERTY_INDUSTRY, PROPERTY_NUMBEROFEMPLOYEES
OBJECTS_LISTS	HubSpot contact/company lists	OBJECTID, PROPERTY_HS_LIST_ID, PROPERTY_HS_NAME, PROPERTY_HS_LIST_TYPE
OBJECTS_WORKFLOWS	Automation workflows	OBJECTID, PROPERTY_HS_NAME, PROPERTY_HS_STATUS

2.3 Association tables

Association tables are the join layer between objects. You need these to connect email events (which carry a contact ID) to deals or companies.

Association Table	What It Links
ASSOCIATIONS_CONTACTS_TO_DEALS	Contact → Deal (join for conversion attribution)
ASSOCIATIONS_CONTACTS_TO_COMPANIES	Contact → Company (account-level analytics)
ASSOCIATIONS_CAMPAIGNS_TO_FORMS	Campaign → Form (form conversion attribution)
ASSOCIATIONS_CONTACTS_TO_FORMS	Contact → Form submission
ASSOCIATIONS_MARKETING_EMAILS_TO_CAMPAIGNS	Email asset → Campaign (links the email content to the campaign)

Critical ID mismatch: the OBJECTID in OBJECTS_CAMPAIGNS is not the same as PROPERTY_HS_EMAIL_CAMPAIGN_ID in event tables. HubSpot uses an internal content/asset ID for that field. Always validate this join in a sample query before building dashboards.

---

3. Method B: Fivetran ETL Connector

How it works

Fivetran is a managed ETL service that extracts data from HubSpot's APIs and loads it into the merchant's own data warehouse. This is the most feature-complete ETL connector for HubSpot marketing analytics. Fivetran handles schema changes automatically, rate limiting, incremental syncs, and retries. It supports all major warehouse destinations including Snowflake, Redshift, BigQuery, and Databricks.

• Requires: any HubSpot tier; Fivetran subscription; data warehouse destination

• All tables land in a schema the merchant names (typically hubspot or hubspot_fivetran)

• Schema changes in HubSpot propagate automatically without full resyncs

• Email event child tables must be individually enabled in the connector Schema tab

3.1 Email and campaign tables

Fivetran shards email events into separate child tables - one table per event type. Each child table must be explicitly enabled in the Fivetran connector settings, or it will be empty.

Table Name	Sync Mode	Notes
EMAIL_CAMPAIGN	Incremental	Campaign-level metadata: name, app_id, counters (sent, opens, clicks) at time of sync
EMAIL_EVENT	Incremental	Parent event table. Must have child tables selected in Schema tab or it won't populate.
EMAIL_EVENT_SENT	Incremental	One row per send. Columns: id, email_campaign_id, email_address, recipient, sent_by, created
EMAIL_EVENT_DELIVERED	Incremental	Delivery confirmation events
EMAIL_EVENT_OPEN	Incremental	Open events. Includes user_agent for device/client analysis
EMAIL_EVENT_CLICK	Incremental	Click events. Includes url (clicked URL) and user_agent
EMAIL_EVENT_BOUNCE	Incremental	Bounce events. Includes bounce_type (HARD/SOFT), status, and reason
EMAIL_EVENT_DEFERRED	Incremental	Temporary delivery deferral events
EMAIL_EVENT_DROPPED	Incremental	Dropped before send (e.g. unsubscribed list). Includes reason field
EMAIL_EVENT_UNSUBSCRIBE	Incremental	Unsubscribe events. Includes portal_id, email_campaign_id
EMAIL_EVENT_SPAM_REPORT	Incremental	Spam complaint events
EMAIL_EVENT_FORWARD	Incremental	Email forward events
EMAIL_EVENT_PRINT	Incremental	Print events (rare, browser print action)

3.2 CRM and supporting tables

Table Name	Sync Mode	Notes
CONTACT	Incremental	All contact properties. Companion: CONTACT_PROPERTY_HISTORY for historical values
COMPANY	Incremental	Company records + COMPANY_PROPERTY_HISTORY
DEAL	Incremental	Deal records. Child tables: DEAL_PROPERTY_HISTORY, DEAL_STAGE. Join to EMAIL events on contact for conversion
FORM	Full	Form definitions (not submissions - use FORM_SUBMISSION)
FORM_SUBMISSION	Incremental	Each form fill. Joinable to contacts for conversion tracking
OWNER	Full	HubSpot user/owner records
ENGAGEMENT	Incremental	Parent engagement table. Child tables per type: NOTE, EMAIL, TASK, MEETING, CALL
CONTACT_COMPANY	Full	Association: contact ↔ company
CONTACT_LIST	Full	HubSpot list definitions
CONTACT_LIST_MEMBER	Full	Which contacts are in which lists
DEAL_PIPELINE	Full	Pipeline definitions and stages for deal tracking
LINE_ITEM_DEAL	Incremental	Association between line items and deals (e-commerce)
TICKET / TICKET_PIPELINE	Incremental	Support tickets and their pipeline stages
WORKFLOW	Full	Automation workflow definitions
SUBSCRIPTION_CHANGE	Incremental	Email subscription changes per contact (opt-in/opt-out history)

3.3 Optional: Fivetran dbt package (dbt_hubspot)

If the merchant runs the Fivetran dbt_hubspot package on top of the raw tables, they will have a set of pre-built analytics models. These are significantly easier to query for funnel analysis and are the preferred layer when available.

dbt Model	What You Get
hubspot__email_campaigns	One row per campaign. Pre-aggregated sent, delivered, open, click, bounce, unsubscribe, spam counts. The go-to table for funnel reporting.
hubspot__email_sends	One row per sent email enriched with whether that specific send was opened, clicked, or bounced.
hubspot__email_events	All email events joined with campaign and contact context, ready for analysis without manual joins.
hubspot__contacts	SCD Type 2 contact model - tracks property changes over time, not just current state.
hubspot__companies	SCD Type 2 company model with engagement activity joined in.
hubspot__deals	Deal model joined to contact engagement - use this to attribute closed deals back to campaigns.
hubspot__engagements	All CRM engagement activities (calls, meetings, notes, tasks) normalized and company/contact-joined.

The dbt package is not auto-installed - a merchant must explicitly configure and run it. Ask during onboarding whether their data team runs dbt on top of Fivetran. If yes, the hubspot__email_campaigns model is the best single table for aggregate campaign funnel analytics.

---

4. Method C: Airbyte ETL Connector

How it works

Airbyte is an open-source (and cloud-hosted) ELT platform. Its HubSpot connector maps each API resource to a stream, which becomes a table in the destination data warehouse. Unlike Fivetran, Airbyte consolidates all email event types into a single email_events table with a type field - there are no separate child tables per event type. Airbyte supports all major warehouse destinations.

• Requires: any HubSpot tier; Airbyte OSS or Cloud; data warehouse destination

• Authentication: HubSpot Private App token or OAuth

• Sync frequency: configurable, from minutes to daily

• Email events: all types in one table (type column = SENT, OPEN, CLICK, BOUNCE, etc.)

Stream (Table in data warehouse)	What It Contains
campaigns	Campaign metadata from the HubSpot Email Campaigns API
marketing_emails	Email asset records including subject line, send date, and campaign association
email_events	All email events in a single table (type field distinguishes SENT, OPEN, CLICK, BOUNCE, etc.) - unlike Fivetran's separate child tables
contacts	Contact records with all properties
contacts_list_memberships	Which lists each contact belongs to
companies	Company records
deals	Deal pipeline records for conversion tracking
deal_pipelines	Pipeline and stage definitions
engagements_calls	Call engagement records
engagements_emails	1:1 CRM email engagements (not marketing emails)
engagements_meetings	Meeting engagements
engagements_notes	Notes attached to CRM records
engagements_tasks	Task records
forms	Form definitions
owners	HubSpot user/owner records
tickets	Support tickets
workflows	Automation workflows
email_subscriptions	Subscription type definitions and contact opt-in status
goals	HubSpot Goals objects
line_items	E-commerce line items associated with deals
products	Product catalogue records
quotes	Sales quote records

Airbyte's email_events table uses a different query pattern than Fivetran. Instead of joining multiple child tables, you filter on the type column: WHERE type = 'OPEN'. Confirm this structure before writing any SQL against an Airbyte-sourced schema.

---

5. Method D: Stitch (Qlik) ETL Connector

How it works

Stitch (now part of Qlik) is a managed ETL tool with a HubSpot connector. Its table structure is similar to Airbyte - a unified email_events table - but with fewer streams than Fivetran. An important limitation: replicating the email_events table requires Super Admin permissions in HubSpot. If the merchant's integration was set up with a lower-permission user, email events will be absent.

• Requires: any HubSpot tier; Stitch subscription; data warehouse destination

• Super Admin required in HubSpot for email_events replication

• Smaller stream library than Fivetran - some engagement sub-types are absent

Table Name	What It Contains
campaigns	Campaign metadata. Primary key: id
email_events	All email events. Requires Super Admin permissions in HubSpot to replicate. Primary key: id
contacts	Contact records with all custom properties flattened. Primary key: canonical_vid
companies	Company records. Primary key: company_id
deals	Deal records. Primary key: deal_id
forms	Form definitions. Primary key: guid
keywords	Portal keywords (SEO tool data). Primary key: keyword_guid
owners	HubSpot owner/user records. Primary key: owner_id
subscription_changes	Email subscription opt-in/opt-out change history
workflows	Automation workflow definitions

Stitch replicates email_events as a unified table with a type field - the same pattern as Airbyte. Query pattern: filter on type rather than joining separate tables.

---

6. Method E and F: Estuary, Windsor, and others

Estuary Flow

Estuary is a newer real-time ELT platform with a HubSpot connector. It uses a streaming-first architecture, meaning data can land in the data warehouse with sub-minute latency. Table structure follows the same logical model as Fivetran/Airbyte but varies by configuration. Less common in merchant stacks as of mid-2026 but growing.

• Key tables: contacts, companies, deals, email_events (unified), marketing_emails, campaigns

• Latency: near real-time (minutes, not hours)

• Well-suited for merchants who need very fresh campaign data

Windsor.ai / Supermetrics

These are reporting-layer tools, not full ELT pipelines. They typically sync aggregated campaign metrics rather than raw event-level data. As a result, they are useful for high-level reporting but insufficient for contact-level funnel analysis. You cannot trace an individual contact's journey from send to conversion.

• Typical tables: hubspot_campaigns (aggregated metrics), hubspot_ads, hubspot_email_performance

• Not suitable for contact-level attribution or funnel analysis

• If a merchant uses only Windsor or Supermetrics, raw event tables will not be present

---

7. Building the Sent → Opened → Clicked → Converted funnel

Regardless of which pipeline method the merchant uses, the funnel logic follows the same pattern. What varies is the table names and how events are stored (sharded vs. unified).

Funnel Stage	Source Table(s)	Notes
Sent	EVENTS_SENT_EMAIL_V2 / EMAIL_EVENT_SENT / email_events	Count distinct OBJECTID or email_address per campaign. The denominator for all other rates.
Delivered	EVENTS_DELIVERED_EMAIL_V2 / EMAIL_EVENT_DELIVERED	Delivery rate = Delivered / Sent. Bounced = Sent - Delivered.
Opened	EVENTS_OPENED_EMAIL_V2 / EMAIL_EVENT_OPEN	Open rate = unique openers / Delivered. Count distinct contact per campaign for unique opens.
Clicked	EVENTS_CLICKED_LINK_IN_EMAIL_V2 / EMAIL_EVENT_CLICK	CTOR = unique clickers / unique openers. Also available: which URLs were clicked.
Converted	OBJECTS_DEALS + ASSOCIATIONS_CONTACTS_TO_DEALS (or FORM_SUBMISSION)	No native email-to-deal event exists. Define conversion as: deal created within N days of a click on the campaign, joined via contact ID.

SQL syntax note: The sample queries below use Snowflake / Redshift-compatible syntax (DATEADD). BigQuery uses DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY) and Databricks uses CURRENT_DATE - INTERVAL 7 DAYS. Adjust accordingly for the merchant's warehouse.

Sample SQL - Fivetran (sharded event tables)

SELECT
  ec.name                              AS campaign_name,
  COUNT(DISTINCT s.email_address)      AS sent,
  COUNT(DISTINCT d.email_address)      AS delivered,
  COUNT(DISTINCT o.email_address)      AS opened,
  COUNT(DISTINCT c.email_address)      AS clicked
FROM email_campaign ec
LEFT JOIN email_event_sent      s ON s.email_campaign_id = ec.id
  AND s.created >= DATEADD('day', -7, CURRENT_DATE)
LEFT JOIN email_event_delivered d ON d.email_campaign_id = ec.id
  AND d.created >= DATEADD('day', -7, CURRENT_DATE)
LEFT JOIN email_event_open      o ON o.email_campaign_id = ec.id
  AND o.created >= DATEADD('day', -7, CURRENT_DATE)
LEFT JOIN email_event_click     c ON c.email_campaign_id = ec.id
  AND c.created >= DATEADD('day', -7, CURRENT_DATE)
GROUP BY ec.name;

Sample SQL - Airbyte/Stitch (unified email_events table)

SELECT
  email_campaign_id,
  COUNT(DISTINCT CASE WHEN type = 'SENT'      THEN recipient END) AS sent,
  COUNT(DISTINCT CASE WHEN type = 'DELIVERED' THEN recipient END) AS delivered,
  COUNT(DISTINCT CASE WHEN type = 'OPEN'      THEN recipient END) AS opened,
  COUNT(DISTINCT CASE WHEN type = 'CLICK'     THEN recipient END) AS clicked
FROM email_events
WHERE created >= DATEADD('day', -7, CURRENT_DATE)
GROUP BY email_campaign_id;

Sample SQL - Native Data Share (sharded, V2_DAILY schema - Snowflake only)

SELECT
  s.PROPERTY_HS_EMAIL_CAMPAIGN_ID      AS campaign_id,
  COUNT(DISTINCT s.OBJECTID)           AS sent,
  COUNT(DISTINCT d.OBJECTID)           AS delivered,
  COUNT(DISTINCT o.OBJECTID)           AS opened,
  COUNT(DISTINCT c.OBJECTID)           AS clicked
FROM V2_DAILY.EVENTS_SENT_EMAIL_V2 s
LEFT JOIN V2_DAILY.EVENTS_DELIVERED_EMAIL_V2 d
  ON d.OBJECTID = s.OBJECTID
  AND d.PROPERTY_HS_EMAIL_CAMPAIGN_ID = s.PROPERTY_HS_EMAIL_CAMPAIGN_ID
LEFT JOIN V2_DAILY.EVENTS_OPENED_EMAIL_V2 o
  ON o.OBJECTID = s.OBJECTID
  AND o.PROPERTY_HS_EMAIL_CAMPAIGN_ID = s.PROPERTY_HS_EMAIL_CAMPAIGN_ID
LEFT JOIN V2_DAILY.EVENTS_CLICKED_LINK_IN_EMAIL_V2 c
  ON c.OBJECTID = s.OBJECTID
  AND c.PROPERTY_HS_EMAIL_CAMPAIGN_ID = s.PROPERTY_HS_EMAIL_CAMPAIGN_ID
WHERE s.OCCURREDAT >= DATEADD('day', -7, CURRENT_DATE)
GROUP BY 1;

---

8. Critical gotchas and onboarding checks

These are the most common failure points encountered when querying HubSpot data in a data warehouse across any pipeline method.

Watch Out For	Detail
Campaign ID mismatch (Native Data Share)	The OBJECTID in OBJECTS_CAMPAIGNS is different from PROPERTY_HS_EMAIL_CAMPAIGN_ID in event tables. HubSpot uses a separate internal content/asset ID. Always verify the join key before writing funnel queries.
Fivetran child tables must be enabled	EMAIL_EVENT only populates if the EMAIL_EVENT_* child tables are explicitly selected in the Fivetran connector's Schema tab. A connector set up without them will have an empty EMAIL_EVENT table and missing email data.
Fivetran 25-hour lookback	Fivetran re-fetches EMAIL_EVENT_* data 25 hours behind the current sync to catch HubSpot's delayed event processing. Expect some duplication in raw tables - use created as the dedup key.
Conversion is not a native event	HubSpot does not emit a 'converted' email event. Conversion must be self-defined: typically a deal created/updated, a form submission, or a purchase event within a time window after a click, joined on contact ID.
Native Data Share requires Ops Hub Pro+ and Snowflake	The HubSpot Native Data Share is only available to merchants on Operations Hub Professional or Enterprise and using Snowflake as their data warehouse. All other warehouse platforms require a third-party ETL connector.
Stitch requires Super Admin for email_events	Stitch specifically requires Super Admin permissions in HubSpot to replicate the email_events table. If the merchant's integration token was set up with a lesser role, email events will be missing.
Airbyte unified vs Fivetran sharded events	Airbyte consolidates all email event types into a single email_events table with a type column. Fivetran splits them into EMAIL_EVENT_SENT, EMAIL_EVENT_OPEN, etc. This changes the query pattern - know which pipeline you're on before writing SQL.
Metadata query syntax varies by warehouse	The discovery query SHOW TABLES IN SCHEMA hubspot; works in Snowflake. Use INFORMATION_SCHEMA.TABLES for BigQuery and Redshift (SELECT table_name FROM information_schema.tables WHERE table_schema = 'hubspot'). Athena uses Glue catalog; Databricks uses SHOW TABLES IN hubspot.

---

9. Onboarding decision matrix

At Sortment's end, this is how we determine what connection method applies and what to request access to.

If the merchant has...	Recommended path for Sortment read access
HubSpot Ops Hub Pro+ and Snowflake as their data warehouse	Request access to their Native Data Share (V2_LIVE or V2_DAILY schema). Zero ETL infrastructure required, freshest data. (Snowflake-only feature.)
Fivetran already running to their data warehouse	Confirm EMAIL_EVENT_* child tables are enabled. Ask for read access to the hubspot schema. If dbt_hubspot is running, prefer the mart models (hubspot__email_campaigns etc.).
Airbyte running to their data warehouse	Request read access to their Airbyte destination schema. Key tables: email_events (unified), campaigns, marketing_emails, contacts, deals.
Stitch running to their data warehouse	Request read access. Verify Super Admin was used for HubSpot auth (required for email_events). Key tables: email_events, campaigns, contacts, deals.
No ETL / no warehouse connection yet	Recommend Fivetran (most feature-complete for HubSpot marketing analytics) - it supports all major warehouse destinations. If they are on Snowflake with Ops Hub Pro+, the HubSpot Native Data Share is the fastest path with no ETL to manage. Fivetran dbt package gives you the cleanest analytics layer out of the box.

---

Appendix: References

• Fivetran HubSpot Connector Documentation

• Fivetran dbt_hubspot Package (GitHub)

• Airbyte HubSpot Connector Documentation

• Stitch HubSpot v4 Documentation

• HubSpot Knowledge Base: Query HubSpot Data in Snowflake

• HubSpot Knowledge Base: Connect Snowflake Data Share

• HubSpot Developer Changelog: Snowflake Data Share Column Changes

• HubSpot Community: Snowflake Data Share ERD