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Data warehouse ⇄ Human resources

Databricks to Jobvite integration — real-time, two-way sync

Keep Databricks and Jobvite in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Why teams connect Databricks and Jobvite

Land the people and organization records from Jobvite in Databricks as live tables for workforce reporting, without extract jobs, and write computed results back where Jobvite can use them.

Workforce data is some of the most requested data in the warehouse and some of the most awkward to move: the record types are many, the fields carry sensitive personal information, the APIs are strict, and hand-built extract jobs go stale or break quietly. Whether Jobvite is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in Databricks next to everything else the company measures.

Stacksync syncs Offer, Candidate, Requisition (Job), Application from Jobvite into tables in Databricks continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Databricks, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Jobvite where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.

Common use cases

  • 01 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 02 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • 03 Two-way sync Candidate records and their Workflow Status between Jobvite and a Postgres database so recruiting-ops teams query and update pipeline data in SQL.
  • 04 Write New Hire records into an HRIS or onboarding system the moment a candidate is marked hired, driven by Jobvite's candidate hired webhook.

Common sync patterns

Queryable history for planning and audit

A continuously synced copy in Databricks gives you a durable, queryable record of how Jobvite's records change over time, for headcount planning and audit questions.

Write-back of computed values

Segments, rollups, or risk flags computed in Databricks sync back onto the matching records in Jobvite, where the HR team sees them in the system they already use.

HR data in the warehouse, minus the pipeline

People and organization records from Jobvite arrive in Databricks as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.

What you can sync between Databricks and Jobvite

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Databricks objects Jobvite objects How this pairing syncs
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Offer Offer state tied to an application (extended, accepted, declined); read out for offer-acceptance reporting and written to downstream comp or HR systems. Change Data Feed is specific to Databricks and Offer to Jobvite — each maps to any object or custom field on the other side.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Candidate Read from the candidate feed (GET /candidate) and written back via POST /candidate/updateCandidates to change status, notes, and disposition on each record. Catalogs is specific to Databricks and Candidate to Jobvite — each maps to any object or custom field on the other side.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Requisition (Job) Job openings created or updated through POST /job and read from GET /jobFeed; maps to opening tables in an ATS reporting warehouse. Schemas is specific to Databricks and Requisition (Job) to Jobvite — each maps to any object or custom field on the other side.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Application Links a candidate to one requisition with its workflow state; read for pipeline reporting and status written back through the candidate update call. Delta Tables is specific to Databricks and Application to Jobvite — each maps to any object or custom field on the other side.
Views Curated read-only projections used as sync sources for downstream tools. Workflow Status The pipeline stage per application (Screen, Interview, Offer, Hired); updated through POST /candidate/updateCandidates to advance records. Views is specific to Databricks and Workflow Status to Jobvite — each maps to any object or custom field on the other side.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. New Hire Hired-candidate records surfaced in the candidate feed and via the candidate hired webhook; commonly written into an HRIS or onboarding tool. Materialized Views is specific to Databricks and New Hire to Jobvite — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Jobvite

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Databricks Jobvite Sub-second propagation

DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.

DeliveryEach detected change is written to Jobvite through its API, with automatic retries and rate-limit backoff.

Jobvite Databricks Sub-second propagation

DetectionJobvite notifies Stacksync of record changes through webhook events. A candidate hired webhook, configured per customer by a Jobvite rep, POSTs to a custom URL on hire/offer-accepted events.

DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
  • Jobvite: Roughly 15 requests per minute and 850 per hour, reset at midnight Pacific, with per-endpoint daily caps (e.g. 20,000/day candidate GET/PUT, 500/day employee sync); 429 on exceed.
What ships with Databricks ⇄ Jobvite

Connect Databricks and Jobvite for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Jobvite connection.

Real-time

Two-way sync

Changes in Databricks or Jobvite instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Jobvite data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Databricks or Jobvite record.

Observability

Monitoring

Track your Databricks ⇄ Jobvite sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and Jobvite.

How the Databricks and Jobvite connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

Jobvite

Integration surface
REST API (JSON) with candidate, requisition (job), and employee feed endpoints under https://api.jobvite.com/{version}
Authentication
API key (api) and secret (sc) plus company ID (companyId), sent in request headers since Jobvite's April 1, 2024 move from URL-query to header-based auth. Credentials are provisioned per customer by Jobvite Support.
Change detection
A candidate hired webhook, configured per customer by a Jobvite rep, POSTs to a custom URL on hire/offer-accepted events; otherwise Stacksync polls the candidate and job feeds on a schedule and diffs results, since records carry no per-item modified-date filter.
Capabilities
read · write · webhooks
Rate limits
Roughly 15 requests per minute and 850 per hour, reset at midnight Pacific, with per-endpoint daily caps (e.g. 20,000/day candidate GET/PUT, 500/day employee sync); 429 on exceed.
Jobvite setup guide
How it works

How to connect Databricks to Jobvite — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Databricks and Jobvite with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Databricks connected
    Jobvite connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and Jobvite objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Databricks ⇄ Jobvite
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Databricks Jobvite
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Jobvite integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

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SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 550 integrations available for Databricks and Jobvite.

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