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Human resources ⇄ Data warehouse

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

Keep Lever and Materialize 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 Materialize

Land the people and organization records from Lever in Materialize 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 Materialize next to everything else the company measures.

Stacksync syncs Notes and Contacts, Opportunities, Postings, Requisitions from Lever into tables in Materialize continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Materialize, 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 Maintain real-time inventory, usage, or account-health counters consumed by customer-facing applications.
  • 02 Bridge streaming sources and non-streaming destinations by materializing joins across both.
  • 03 Push Postings and Requisitions into an HRIS or warehouse to reconcile approved headcount against open roles.
  • 04 When an Opportunity is marked hired, write the candidate and its Offer into an HRIS or onboarding system to start employee provisioning.

Common sync patterns

HR data in the warehouse, minus the pipeline

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

Headcount and cost joined with everything else

Analysts combine Lever's workforce records with finance, product, or operational data already in Materialize for reporting the HR system cannot produce on its own.

Fresh data instead of last night's load

Because changes stream continuously, reports query current workforce data rather than waiting for an overnight load window to finish.

What you can sync between Lever and Materialize

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 Materialize objects How this pairing syncs
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. Materialized Views Incrementally maintained query results that syncs read as continuously up-to-date datasets. Requisitions is specific to Lever and Materialized Views to Materialize — each maps to any object or custom field on the other side.
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. Sinks Outbound connections that emit view changes to Kafka topics. Offers is specific to Lever and Sinks to Materialize — 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. Indexes In-memory arrangements that make view reads fast for serving workloads. Users is specific to Lever and Indexes to Materialize — 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. Clusters Compute pools that isolate ingestion, view maintenance, and serving. Stages is specific to Lever and Clusters to Materialize — 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. Connections & Secrets Stored credentials and endpoints used by sources and sinks. Feedback is specific to Lever and Connections & Secrets to Materialize — 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. Schemas & Databases Namespaces that organize objects a sync targets. Interviews is specific to Lever and Schemas & Databases to Materialize — each maps to any object or custom field on the other side.

How changes propagate between Lever and Materialize

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

Materialize Lever Sub-second propagation

DetectionChanges in Materialize are captured at the source via change data capture — no polling loop against its API. SUBSCRIBE queries stream row-level changes of any view or table to the client.

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 ⇄ Materialize

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Lever or Materialize 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 Materialize record.

Observability

Monitoring

Track your Lever ⇄ Materialize 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 Materialize.

How the Lever and Materialize 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

Materialize

Integration surface
PostgreSQL wire protocol (SQL)
Authentication
Database credentials (username/password; app passwords in the managed cloud service)
Change detection
SUBSCRIBE queries stream row-level changes of any view or table to the client
Capabilities
read · write · CDC
How it works

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

    Choose tables

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

Lever and Materialize 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

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