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Human resources ⇄ Database

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

Keep Lever and MongoDB 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 Lever and MongoDB

Put your workforce data where your apps can reach it: MongoDB 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. MongoDB is where internal tools, dashboards, provisioning jobs, and analytics actually read and store records. The overlap is the workforce itself: Stages, Feedback, Interviews, Notes and Contacts in Lever need to exist as queryable Change streams, GridFS files, Databases, Collections in MongoDB 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 Change streams, GridFS files, Databases, Collections in MongoDB with Stages, Feedback, Interviews, Notes and Contacts 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 Capture change stream events and propagate them to SaaS tools in near real time instead of running batch exports.
  • 02 Keep a MongoDB-backed product catalog aligned with an ERP's item master in both directions.
  • 03 Consolidate Feedback, Interviews, and Notes into a warehouse for interviewer scorecard and time-to-fill reporting.
  • 04 Write enriched Sources, Tags, and Contact data back onto Opportunities from an outbound sourcing pipeline.

Common sync patterns

Org and structure stay aligned

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

Computed and operational fields flow back

Values assembled or corrected in MongoDB 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 Change streams, GridFS files, Databases, Collections in MongoDB, so internal apps and dashboards read live data instead of a periodic export.

What you can sync between Lever and MongoDB

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.

Lever objects MongoDB objects How this pairing syncs
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. Collections The table-like sync unit; each collection maps to a table or object in the paired system. Offers is specific to Lever and Collections to MongoDB — each maps to any object or custom field on the other side.
Users Lever team members (recruiters, hiring managers) with configurable roles; can be created via POST /users, deactivated, and reactivated through the API. Documents BSON records created, updated, and deleted during syncs, keyed by _id. Users is specific to Lever and Documents to MongoDB — each maps to any object or custom field on the other side.
Stages Pipeline stage definitions that Opportunities move through; read to model funnel state and stage transitions in a database. Embedded documents and arrays Nested structures that syncs flatten or map to related records in relational targets. Stages is specific to Lever and Embedded documents and arrays to MongoDB — each maps to any object or custom field on the other side.
Feedback Interview feedback and scorecard forms attached to Opportunities; created via POST /opportunities/:id/feedback and consolidated into a warehouse for interviewer analytics. Indexes Keep lookups by sync key fast on large collections. Feedback is specific to Lever and Indexes to MongoDB — each maps to any object or custom field on the other side.
Interviews Scheduled interview panel events with times and interviewers; read for scheduling reporting and time-to-hire metrics, and creatable via the panels endpoint. Views Read-only aggregation-defined sources for filtered sync datasets. Interviews is specific to Lever and Views to MongoDB — each maps to any object or custom field on the other side.
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. Change streams The oplog-backed event feed that powers real-time change capture. Notes and Contacts is specific to Lever and Change streams to MongoDB — each maps to any object or custom field on the other side.

How changes propagate between Lever and MongoDB

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.

Lever MongoDB 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 MongoDB as a row-level write, with types converted between the two schemas.

MongoDB Lever Sub-second propagation

DetectionChanges in MongoDB are captured at the source via change data capture — no polling loop against its API. MongoDB oplog and change streams (requires the database to run as a replica set — even single-node).

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

Rate-limit considerations

  • 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 Lever ⇄ MongoDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Lever or MongoDB 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 Lever or MongoDB record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Lever and MongoDB connectors work

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

MongoDB

Integration surface
MongoDB wire protocol via official drivers; Atlas additionally offers an administration REST API for cluster management
Authentication
Database credentials (username/password) or TLS/SSL X.509 certificate (.pem upload), entered individually or via a MongoDB connection string (SRV or standard); Stacksync IP allowlisting required
Change detection
MongoDB oplog and change streams (requires the database to run as a replica set — even single-node); Stacksync leverages these built-in tools to track changes in real time
Capabilities
read · write · CDC
MongoDB setup guide
How it works

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

    Choose tables

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

Lever and MongoDB 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
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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 540 integrations available for Lever and MongoDB.

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