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Data warehouse ⇄ Human resources

Google Cloud Platform to Lever integration — real-time, two-way sync

Keep Google Cloud Platform and Lever 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Google Cloud Platform and Lever

Land the people and organization records from Lever in Google Cloud Platform as live tables for workforce reporting, without extract jobs, and write computed results back where Lever 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 Lever is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in Google Cloud Platform next to everything else the company measures.

Stacksync syncs Opportunities, Postings, Requisitions, Offers from Lever into tables in Google Cloud Platform continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Google Cloud Platform, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Lever 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 Publish change events to Pub/Sub so downstream services react to record updates as they happen.
  • 02 When an Opportunity is marked hired, write the candidate and its Offer into an HRIS or onboarding system to start employee provisioning.
  • 03 Consolidate Feedback, Interviews, and Notes into a warehouse for interviewer scorecard and time-to-fill reporting.

Common sync patterns

Queryable history for planning and audit

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

Write-back of computed values

Segments, rollups, or risk flags computed in Google Cloud Platform sync back onto the matching records in Lever, 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 Lever arrive in Google Cloud Platform as queryable tables, current within seconds instead of a day behind, replacing hand-built extract jobs.

What you can sync between Google Cloud Platform and Lever

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.

Google Cloud Platform objects Lever objects How this pairing syncs
Firestore documents Document data read and written through the Firestore API for app-facing syncs. Users Lever team members (recruiters, hiring managers) with configurable roles; can be created via POST /users, deactivated, and reactivated through the API. Firestore documents is specific to Google Cloud Platform and Users to Lever — each maps to any object or custom field on the other side.
Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. Stages Pipeline stage definitions that Opportunities move through; read to model funnel state and stage transitions in a database. Spanner tables is specific to Google Cloud Platform and Stages to Lever — each maps to any object or custom field on the other side.
BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. Feedback Interview feedback and scorecard forms attached to Opportunities; created via POST /opportunities/:id/feedback and consolidated into a warehouse for interviewer analytics. BigQuery datasets is specific to Google Cloud Platform and Feedback to Lever — each maps to any object or custom field on the other side.
BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. Interviews Scheduled interview panel events with times and interviewers; read for scheduling reporting and time-to-hire metrics, and creatable via the panels endpoint. BigQuery tables is specific to Google Cloud Platform and Interviews to Lever — each maps to any object or custom field on the other side.
Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. Notes and Contacts Free-text Notes on Opportunities plus the underlying Contact (person) that dedupes multiple Opportunities; notes are posted via POST /opportunities/:id/notes and contact-level tags, sources, and links can be added back for attribution. Cloud SQL databases is specific to Google Cloud Platform and Notes and Contacts to Lever — each maps to any object or custom field on the other side.
Cloud Storage objects Staging area for file-based bulk loads into BigQuery and other services. Opportunities The core pipeline record for a candidate applying to a role; replaced the deprecated Candidates endpoint. Created via POST /opportunities and updated (stage, archive, links, tags, sources, files) through the API, and synced two-way with a database or HRIS. Cloud Storage objects is specific to Google Cloud Platform and Opportunities to Lever — each maps to any object or custom field on the other side.

How changes propagate between Google Cloud Platform and Lever

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.

Google Cloud Platform Lever Sub-second propagation

DetectionGoogle Cloud Platform pushes changes as they happen — webhook events backed by change data capture. Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery.

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

Lever Google Cloud Platform Sub-second propagation

DetectionLever notifies Stacksync of record changes through webhook events. Webhooks for candidate and application lifecycle events (applicationCreated, candidateStageChange, candidateArchiveStateChange, candidateHired,.

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

Rate-limit considerations

  • Google Cloud Platform: Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits.
  • Lever: 10 requests/second per API key with a token-bucket burst to ~20/s; POSTs that create candidates/applications are throttled to roughly 2/second. Sustained overage returns 429 with Retry-After. List endpoints are cursor-paginated at up to 100 records per page.
What ships with Google Cloud Platform ⇄ Lever

Connect Google Cloud Platform and Lever for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud Platform–Lever connection.

Real-time

Two-way sync

Changes in Google Cloud Platform or Lever instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Google Cloud Platform or Lever 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 Google Cloud Platform or Lever record.

Observability

Monitoring

Track your Google Cloud Platform ⇄ Lever sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Google Cloud Platform and Lever.

How the Google Cloud Platform and Lever connectors work

Google Cloud Platform

Integration surface
Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols
Authentication
IAM service accounts with OAuth 2.0 tokens
Change detection
Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery tables
Capabilities
read · write · CDC · webhooks
Rate limits
Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits

Lever

Integration surface
REST Data API (api.lever.co/v1)
Authentication
API key over HTTP Basic auth (key as username, blank password) for internal integrations, or OAuth 2.0 with 1-hour access tokens for partner integrations (auth.lever.co)
Change detection
Webhooks for candidate and application lifecycle events (applicationCreated, candidateStageChange, candidateArchiveStateChange, candidateHired, interview created/updated/deleted), plus incremental polling via created_at and updated_at range filters on Opportunities
Capabilities
read · write · webhooks
Rate limits
10 requests/second per API key with a token-bucket burst to ~20/s; POSTs that create candidates/applications are throttled to roughly 2/second. Sustained overage returns 429 with Retry-After. List endpoints are cursor-paginated at up to 100 records per page.
Lever setup guide
How it works

How to connect Google Cloud Platform to Lever — 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 Google Cloud Platform and Lever 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
    Google Cloud Platform connected
    Lever connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Google Cloud Platform and Lever 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 · Google Cloud Platform ⇄ Lever
    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
    Google Cloud Platform Lever
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Google Cloud Platform and Lever 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.

Learn more about security
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DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

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 539 integrations available for Google Cloud Platform and Lever.

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