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Database ⇄ Human resources

Elasticsearch to Lever integration — real-time, two-way sync

Keep Elasticsearch 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 Elasticsearch and Lever

Put your workforce data where your apps can reach it: Elasticsearch and Lever share the same people, positions, and org structure in real time.

Lever is the system of record for the people side of the business — employees, candidates, roles, and the org structure around them. Elasticsearch is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Offers, Users, Stages, Feedback in Lever need to exist as queryable Index templates, Indices, Documents, Index mappings in Elasticsearch before an app can act on them. When that bridge is a nightly export or a hand-run CSV, every downstream system spends the day working from a roster that has already moved on.

Stacksync syncs Index templates, Indices, Documents, Index mappings in Elasticsearch with Offers, Users, Stages, Feedback in Lever field by field, in real time. You decide which system owns which fields — Lever typically owns identity and org attributes, while operational or computed values can flow back the other way — and Stacksync keeps every copy consistent, matching records on a stable key and resolving conflicts by rules you set.

The result is one live picture of the workforce on both sides: HR keeps its source of truth, and the database keeps a current mirror that internal apps, reports, and access controls can trust without a batch window in between.

Common use cases

  • 01 Push product catalog data from an ERP or commerce database into Elasticsearch for storefront search.
  • 02 Mirror support tickets into an index used for full-text search and agent-assist tooling.
  • 03 Write enriched Sources, Tags, and Contact data back onto Opportunities from an outbound sourcing pipeline.
  • 04 Two-way sync Opportunities and their Stages between Lever and a Postgres database so recruiting ops and analysts query the pipeline in SQL while recruiters keep working in Lever.

Common sync patterns

Org and structure stay aligned

Groups, departments, managers, and reporting lines from Lever stay consistent in Elasticsearch, so hierarchy-driven logic and permissions don't drift.

Computed and operational fields flow back

Values assembled or corrected in Elasticsearch write onto the matching record in Lever where those fields are writable, keeping the people system enriched.

Mirror people records into the database

Records maintained in Lever land as queryable Index templates, Indices, Documents, Index mappings in Elasticsearch, so internal apps and dashboards read live data instead of a periodic export.

What you can sync between Elasticsearch 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.

Elasticsearch objects Lever objects How this pairing syncs
Data streams Append-only targets for time-series or event data pushed from source systems. Interviews Scheduled interview panel events with times and interviewers; read for scheduling reporting and time-to-hire metrics, and creatable via the panels endpoint. Data streams is specific to Elasticsearch and Interviews to Lever — each maps to any object or custom field on the other side.
Ingest pipelines Server-side transforms applied to documents as a sync writes them. 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. Ingest pipelines is specific to Elasticsearch and Notes and Contacts to Lever — each maps to any object or custom field on the other side.
Index templates Reusable settings and mappings applied automatically to new indices a sync creates. 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. Index templates is specific to Elasticsearch and Opportunities to Lever — each maps to any object or custom field on the other side.
Indices Target containers for synced records; each holds a table-like collection of JSON documents. Postings Job posting records with categories, apply URLs, workplace type, and requisition codes. Can be created via POST /postings and read into a warehouse for open-role reporting. Indices is specific to Elasticsearch and Postings to Lever — each maps to any object or custom field on the other side.
Documents The unit of sync; JSON records created, updated, and deleted by _id. Requisitions Headcount/requisition records with custom requisition fields, tied to Postings; read via GET /requisitions and synced to an HRIS to reconcile approved headcount against open roles. Documents is specific to Elasticsearch and Requisitions to Lever — each maps to any object or custom field on the other side.
Index mappings Field type definitions that determine how synced fields are indexed and queried. Offers Offer records attached to an Opportunity with status and offer-form fields; exposed read-only through GET /opportunities/:id/offers, so they sync outbound to an HRIS or onboarding system when a candidate reaches the offer stage. Index mappings is specific to Elasticsearch and Offers to Lever — each maps to any object or custom field on the other side.

How changes propagate between Elasticsearch 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.

Elasticsearch Lever Interval-based propagation

DetectionStacksync polls Elasticsearch for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp or sequence fields.

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

Lever Elasticsearch 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 written to Elasticsearch through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Elasticsearch: No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity.
  • 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 Elasticsearch ⇄ Lever

Connect Elasticsearch and Lever for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Elasticsearch 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 Elasticsearch or Lever record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Elasticsearch and Lever.

How the Elasticsearch and Lever connectors work

Elasticsearch

Integration surface
REST API (JSON over HTTP)
Authentication
API keys or basic authentication; Elastic Cloud also issues service account tokens
Change detection
Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
Capabilities
read · write
Rate limits
No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity

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 Elasticsearch 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 Elasticsearch 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
    Elasticsearch connected
    Lever connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Elasticsearch 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 · Elasticsearch ⇄ 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
    Elasticsearch Lever
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Elasticsearch 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.

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ISO 27001
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DPF US-EU-UK-CH
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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 520 integrations available for Elasticsearch and Lever.

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