Teamtailor connector
Set up the Teamtailor connector in Kaivo: authentication, configuration, the 16 BigQuery tables it syncs, and answers to common questions.
Written By Lauri Raivio
Last updated 16 days ago
Kaivo is a fully managed data platform that syncs your Teamtailor data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your HR data instead of moving it.
What is the Teamtailor connector
Sync your Teamtailor candidates, jobs, and applications into BigQuery with Kaivo to report on recruiting alongside the rest of your data.
Getting started with the Teamtailor connector
- Sign up for Kaivo and create a workspace.
- Connect your Teamtailor account.
- Choose which tables to sync.
- Wait for the initial sync to finish.
- Query your data in BigQuery or your favourite AI or BI tool.
Authenticating Teamtailor
Authenticate with your API Key.
Tables and columns synced from Teamtailor
Kaivo syncs 16 tables from Teamtailor into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
candidate_activities (12 columns)
candidate_activities (12 columns)
candidates (29 columns)
candidates (29 columns)
Subtable: candidates__tags
Subtable: candidates__activities
Subtable: candidates__job_applications
Subtable: candidates__questions
Subtable: candidates__answers
Subtable: candidates__locations
Subtable: candidates__regions
Subtable: candidates__uploads
Subtable: candidates__custom_field_values
Subtable: candidates__partner_results
departments (5 columns)
departments (5 columns)
Subtable: departments__roles
Subtable: departments__teams
job_activities (12 columns)
job_activities (12 columns)
job_applications (20 columns)
job_applications (20 columns)
jobs (40 columns)
jobs (40 columns)
Subtable: jobs__tags
Subtable: jobs__activities
Subtable: jobs__locations
Subtable: jobs__questions
Subtable: jobs__picked_questions
Subtable: jobs__candidates
Subtable: jobs__stages
Subtable: jobs__team_memberships
Subtable: jobs__colleagues
Subtable: jobs__regions
Subtable: jobs__custom_fields
Subtable: jobs__custom_field_values
locations (14 columns)
locations (14 columns)
Subtable: locations__teams
regions (6 columns)
regions (6 columns)
Subtable: regions__locations
reject_reasons (6 columns)
reject_reasons (6 columns)
Subtable: reject_reasons__job_applications
roles (7 columns)
roles (7 columns)
Subtable: roles__teams
stages (15 columns)
stages (15 columns)
Subtable: stages__job_applications
Subtable: stages__triggers
team_memberships (8 columns)
team_memberships (8 columns)
teams (9 columns)
teams (9 columns)
Subtable: teams__users
Subtable: teams__jobs
Subtable: teams__departments
Subtable: teams__roles
Subtable: teams__locations
todos (15 columns)
todos (15 columns)
user_activities (12 columns)
user_activities (12 columns)
users (31 columns)
users (31 columns)
Subtable: users__role_addons
Subtable: users__team_memberships
Subtable: users__activities
Subtable: users__jobs
Subtable: users__notification_settings
How the Teamtailor sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Teamtailor supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.
Frequently asked questions
How long does the initial sync take for Teamtailor?
It depends on how much history is in your Teamtailor account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.
Can I sync only some tables or columns?
Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.
What happens when Teamtailor's schema changes?
New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in Teamtailor, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.
How do I handle GDPR or data deletion requests?
Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in Teamtailor instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the Teamtailor connector in Kaivo and all of its synced data is deleted with it.
Common use cases for Teamtailor data
Pipeline funnel
Track applications by stage to measure your hiring funnel and conversion.
Time to hire
Analyse applications to measure time to hire and where candidates stall.
Source effectiveness
Report on where candidates come from to see which channels produce hires.
Job performance
Break hiring down by job and department to monitor open roles and progress.
Use Teamtailor data in your AI and BI tools
Once Teamtailor data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with Teamtailor data.
Claude
Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →
Power BI
Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →
Data Studio
Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →
Tableau
The premium analytics standard, with native BigQuery integration. Setup guide →
Google Sheets
Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →
Excel
Connect via Power Query's BigQuery connector. Setup guide →
Metabase
Open-source BI tool with strong BigQuery support. Setup guide →
See our pricing page for Teamtailor connector pricing and plan details.
Related connectors
- Greenhouse: Sync Greenhouse to BigQuery.
- Kellokortti: Sync Kellokortti to BigQuery.
- Nepton: Sync Nepton to BigQuery.
- 7shifts: Sync 7shifts to BigQuery.
- Ashby: Sync Ashby to BigQuery.
- BambooHR: Sync BambooHR to BigQuery.
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