Can you integrate Elasticsearch with Lever?

Explore a Elasticsearch and Lever integration with a Stacksync engineer. Stacksync support for Elasticsearch and Lever is not established by the connector documentation reviewed for this page. Start with one record and the update your business needs to identify an implementation path.

Can Elasticsearch and Lever sync in both directions?

Confirm two-way support with Stacksync for the records and fields you need in both systems. Access to a vendor API does not confirm that its Stacksync connector supports write-back.

What should be ready before the Elasticsearch and Lever initial load?

Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Identify the Elasticsearch account, edition, environment, and business objects the integration must access. Identify the Lever account, edition, environment, and business objects the integration must access. Use the pair worksheet to record ownership and acceptance criteria.

How fast does the Elasticsearch to Lever sync run?

Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.

Will existing duplicates merge automatically?

No. Stacksync documents that pre-existing duplicates are not merged automatically when two-way sync begins. Review the initial dataset and matching plan before enabling it; an empty destination can simplify the first load.

How do I map Elasticsearch fields to Lever?

Start with one business entity and a stable record ID. Map a small set of editable fields with compatible types, test required values and relationships, then expand after the pilot passes.

What should I do if a record fails to sync?

Check the destination error, field constraints, permissions, and current source value. The Stacksync issues dashboard supports retry and revert; retry reads current source values, so verify the intended record state before acting.

What does a Elasticsearch and Lever integration cost?

Use the current Stacksync pricing page and confirm the supported implementation with the team. Scope the required objects, record volume, update frequency, initial load, and support needs when comparing a managed connector with native or custom development.

Which records should the Elasticsearch and Lever pilot start with?

Start by reviewing Proposed application user or identity table in Elasticsearch (choose its name) in Elasticsearch and Users in Lever. Check how these records relate in your workflow, then confirm the actual fields and supported operations. Test record matching and one failed or repeated update before adding more records.

Database / Human resources · Two-way sync platform

Elasticsearch and Lever integration

Plan how Elasticsearch and Lever should share data across your business. Work with Stacksync engineers on record mapping, system access, and the requirements for running the integration.

Scope your workflow with an integration engineer
Review the systems, records, and updates you need

Integration planning

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Elasticsearch

Lever

Review the integration scope

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Proposed workflow

Application user or identity reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting eventA change involving the proposed application user or identity table in Elasticsearch or Lever Users needs a defined result in the other system.

Start with the proposed application user or identity table in Elasticsearch and Lever Users. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve tenant and group references and establish a protected administrative-account policy.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

What to verifyTest a renamed login, disabled account, missing group, and a user existing in two tenants.

Review records and field ownership

Proposed record relationships

Records to connect

Use these examples to define record matching and field ownership for your technical review.

Download the mapping worksheet

CSV · No email required

Example record relationships between Elasticsearch and Lever
Elasticsearch record	Lever record	Record matching	Field ownership
Proposed application user or identity tableProposed table; choose its name and schema.Reporting dataset	UsersProposed record; confirm Stacksync object support.	Use the immutable user ID within the tenant or directory. Do not equate an application user with a CRM customer contact.	Identity and application owners approve account lifecycle and access changes; synchronize only approved attributes.
Proposed deal or opportunity tableProposed table; choose its name and schema.Reporting dataset	OpportunitiesProposed record; confirm Stacksync object support.	Keep the opportunity/deal ID separate from any later order or invoice ID.	The sales process owns qualification and stage changes; downstream financial records have their own state and approval rules.

These relationships do not establish connector availability. Review the required connection and record operations with Stacksync.

Record coverage to review

Use documented coverage where available. Catalog record types are starting points for review and do not confirm Stacksync support.

Elasticsearch

Connection and object support require review

Record types to review with Stacksync

Record types	Coverage and requirements
Indices Documents Index mappings Aliases Data streams Ingest pipelines	Confirm support for this record type and the direction you need.

Discuss Elasticsearch requirements

Lever

Connection and object support require review

Record types to review with Stacksync

Record types	Coverage and requirements
Opportunities Postings Requisitions Offers Users Stages	Confirm support for this record type and the direction you need.

Discuss Lever requirements

Connection essentials

Confirm Stacksync support and account requirements for undocumented connections. Interface information alone does not establish connector availability.

View setup requirements and limits

Connection requirement	Elasticsearch	Lever
Integration interface	REST API (JSON over HTTP)	REST Data API (api.lever.co/v1)
Authentication	Confirm the credentials, API plan, and permissions required for Elasticsearch.	Confirm the credentials, API plan, and permissions required for Lever.
Change detection	Confirm how Stacksync detects changes for this connector and the objects you need.	Confirm how Stacksync detects changes for this connector and the objects you need.
Read access	Confirm with Stacksync	Confirm with Stacksync
Write access	Confirm with Stacksync	Confirm with Stacksync

Enterprise controls

Security and control for your integrations

Explore security controls

Compliance and data transfers

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.

SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH

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:

Record-level recovery

Inspect sync errors and use retry and revert controls to resolve failed updates.

Read the recovery guide

Implementation

Technical reference

Review setup, record relationships, testing, and recovery for your implementation.

Authentication, permissions and API limits

Connection requirements and limits

Elasticsearch

Integration interface: REST API (JSON over HTTP)
Authentication: Confirm the credentials, API plan, and permissions required for Elasticsearch.
Change detection: Confirm how Stacksync detects changes for this connector and the objects you need.
Read access: Confirm with Stacksync
Write access: Confirm with Stacksync

Setup requirements

Identify the Elasticsearch account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Elasticsearch, including read/write support, authentication, and initial-load limits.

Limitations to check

Confirm Stacksync support for Elasticsearch and the record types your workflow needs.
Review write-back, deletion handling, update timing, and account limits with the integration team.

Lever

Integration interface: REST Data API (api.lever.co/v1)
Authentication: Confirm the credentials, API plan, and permissions required for Lever.
Change detection: Confirm how Stacksync detects changes for this connector and the objects you need.
Read access: Confirm with Stacksync
Write access: Confirm with Stacksync

Setup requirements

Identify the Lever account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Lever, including read/write support, authentication, and initial-load limits.

Limitations to check

Confirm Stacksync support for Lever and the record types your workflow needs.
Review write-back, deletion handling, update timing, and account limits with the integration team.

Technical documentation

Lever vendor API documentation

Prepare Elasticsearch and Lever access

Set up both accounts before testing the mapping. Use test records where available, and identify the account administrator who can approve access and help resolve setup errors.

Elasticsearch setup checklist

Identify the Elasticsearch account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Elasticsearch, including read/write support, authentication, and initial-load limits.

Lever setup checklist

Identify the Lever account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Lever, including read/write support, authentication, and initial-load limits.

Prepare to go live

Record the fields each system can update, the first-load cutoff, both record IDs, the expected update delay, and who handles errors. Complete the tests before production before expanding to more records.

Use the Elasticsearch and Lever planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.

Talk to an engineer · Review current pricing

Record identity and field ownership

Use these data-model references to describe the records your connection needs. They are planning examples; connector availability and supported operations must be established before implementation.

Download the mapping worksheet · CSV, no email required

Reporting dataset

Proposed application user or identity table in Elasticsearch (choose its name) / Users

Plan a application user or identity dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Elasticsearch: Your database schema
Lever: Object support to establish
Record identity: Use the immutable user ID within the tenant or directory. Do not equate an application user with a CRM customer contact.
Field ownership: Identity and application owners approve account lifecycle and access changes; synchronize only approved attributes.

Fields to include

Source user ID
Tenant reference
Account status
Group references

Record dependencies: Resolve tenant and group references and establish a protected administrative-account policy.
Validation: Test a renamed login, disabled account, missing group, and a user existing in two tenants.
Recovery: Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.

References: Lever: Users documentation

Reporting dataset

Proposed deal or opportunity table in Elasticsearch (choose its name) / Opportunities

Plan a deal or opportunity dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Elasticsearch: Your database schema
Lever: Object support to establish
Record identity: Keep the opportunity/deal ID separate from any later order or invoice ID.
Field ownership: The sales process owns qualification and stage changes; downstream financial records have their own state and approval rules.

Fields to include

Source deal ID
Stage
Amount and currency
Expected close date
Company reference

Record dependencies: Map the customer and sales pipeline before the opportunity; map stage values deliberately.
Validation: Test a reopened won deal, a stage with no destination equivalent, and an amount using a different currency.
Recovery: Suspend downstream creation for a rejected deal and review whether an order already exists before retrying.

References: Lever: Opportunities documentation

Compare integration approaches

Choose a method around one example record and the update your business needs. Use Proposed application user or identity table in Elasticsearch (choose its name) / Users to review record matching and confirm Stacksync support for the required operations. Compare ongoing sync, a custom workflow, and a scheduled export against that requirement.

Stacksync managed sync

Best fit: Review compatibility with a Stacksync engineer using an example of the records and updates you need.
Operating responsibility: Fits ongoing record synchronization when the required operations are supported. Add workflow steps for approvals or business actions that go beyond copying fields.
Before you choose: Check record matching: Use the immutable user ID within the tenant or directory. Do not equate an application user with a CRM customer contact. Verify field coverage, deletion handling, and how changes are detected.

Native vendor integration

Best fit: A vendor-built integration may fit if it supports your Elasticsearch and Lever record types.
Operating responsibility: Can reduce setup for a supported workflow. You may need another method for records or business steps it does not cover.
Before you choose: First check whether either vendor offers this integration. If available, verify Proposed application user or identity table in Elasticsearch (choose its name) / Users, update direction, account tier, and related-record handling.

Custom API or workflow

Best fit: Consider when Elasticsearch and Lever need a transformation, approval, or action outside a direct record sync.
Operating responsibility: Provides control over business steps; the team owns credentials, version changes, error queues, and reconciliation.
Before you choose: Verify endpoint permissions, pagination, quotas, duplicate detection, and failure recovery.

File or scheduled snapshot

Best fit: Consider for a one-time Elasticsearch / Lever migration or a reporting need with an explicit freshness window.
Operating responsibility: Can simplify a bounded transfer; later changes and deletion history require another extraction or a separately designed incremental process.
Before you choose: Record the extraction cutoff, source IDs, encoding, date/number formats, and reconciliation totals.

Workflow scenarios and expected results

Application user or identity reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting event: A change to the selected Proposed application user or identity table in Elasticsearch (choose its name) or Users record needs a defined result in the other system.

Start with Elasticsearch Proposed application user or identity table in Elasticsearch (choose its name) and Lever Users. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve tenant and group references and establish a protected administrative-account policy.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Test a renamed login, disabled account, missing group, and a user existing in two tenants.

If it fails: Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.

Deal or opportunity reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting event: A change to the selected Proposed deal or opportunity table in Elasticsearch (choose its name) or Opportunities record needs a defined result in the other system.

Start with Elasticsearch Proposed deal or opportunity table in Elasticsearch (choose its name) and Lever Opportunities. Use the record-matching and field-ownership rules from your mapping worksheet.
Map the customer and sales pipeline before the opportunity; map stage values deliberately.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.

Expected result: Test a reopened won deal, a stage with no destination equivalent, and an amount using a different currency.

If it fails: Suspend downstream creation for a rejected deal and review whether an order already exists before retrying.

Worker lifecycle planning for Lever and Elasticsearch

This is an evaluation scenario; connector and operation support require confirmation.

Starting event: A worker joins, moves, or leaves in Lever; a downstream process in Elasticsearch needs the approved context.

Identify the worker and employment record represented by Opportunities or Users. Retain effective dates and organizational scope.
Determine what Documents represents: an operational task, a user identity, or a reporting row. Define a relationship; do not map these records as if they were the employee itself.
Require the process owner to approve any access, payroll, or account action and assign an exception owner.

Expected result: Rehires and concurrent assignments keep distinct employment context; delayed updates do not reverse a newer effective state.

If it fails: Inspect employment identity and effective dates before retrying the downstream action.

Initial load and acceptance testing

Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.

Proposed application user or identity table in Elasticsearch (choose its name) / Users

Test case

Test a renamed login, disabled account, missing group, and a user existing in two tenants.

Expected result

The expected application user or identity relationship is preserved with no duplicate action or unintended write.

Proposed deal or opportunity table in Elasticsearch (choose its name) / Opportunities

Test case

Test a reopened won deal, a stage with no destination equivalent, and an amount using a different currency.

Expected result

The expected deal or opportunity relationship is preserved with no duplicate action or unintended write.

Direction and permissions

Test case

Bring an example source record and the intended destination operation to the compatibility review. Confirm the supported route before granting write access.

Expected result

Only an approved, supported direction and permitted fields are written.

Freshness and reconciliation

Test case

Measure source and destination times for the selected records under normal load and a burst. Reconcile IDs and values using the same filters and cutoff.

Expected result

The process meets its agreed freshness target and reconciliation has no unexplained differences.

Failed updates, retries and recovery

Start with the failed record and the destination error, then inspect the source value, field requirements, and access.

Rejected or repeated application user or identity change

Investigate

Inspect Elasticsearch Proposed application user or identity table in Elasticsearch (choose its name) and Lever Users, their IDs, and the destination error.

Next action

Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.

Rejected or repeated deal or opportunity change

Investigate

Inspect Elasticsearch Proposed deal or opportunity table in Elasticsearch (choose its name) and Lever Opportunities, their IDs, and the destination error.

Next action

Suspend downstream creation for a rejected deal and review whether an order already exists before retrying.

A record type or update is unavailable

Investigate

Check the Elasticsearch and Lever connector guides, account permissions, and any operations marked On Request.

Next action

Ask the integration team to confirm a supported way to handle that record. Verify whether it needs connector configuration or a separate workflow step.

Source and destination disagree after a retry

Investigate

Compare current source values, destination validation, identity mappings, and any side effects already completed.

Next action

Stacksync issue retry reads the current source state. Decide the intended state before retrying or reverting; reconcile downstream effects separately.

Read the Stacksync issues dashboard guide for retry and revert behavior.

Change detection and update delivery

How updates move between Elasticsearch and Lever

See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.

Elasticsearch Lever Direction requires confirmation

Detect changesConfirm how Stacksync detects changes for this connector and the objects you need.

Apply updatesConfirm that Stacksync can create or update the records you need in Lever.

Lever Elasticsearch Direction requires confirmation

Detect changesConfirm how Stacksync detects changes for this connector and the objects you need.

Apply updatesConfirm that Stacksync can create or update the records you need in Elasticsearch.

Update timing and record limits

Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
Review write-back, deletion handling, update timing, and account limits with the integration team.
Review write-back, deletion handling, update timing, and account limits with the integration team.

FAQ