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Data warehouse ⇄ Human resources

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

Keep Greenplum 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 Greenplum and Lever

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

Stacksync syncs Interviews, Notes and Contacts, Opportunities, Postings from Lever into tables in Greenplum continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Greenplum, 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 Consolidate data from multiple source systems into partitioned Greenplum fact tables.
  • 02 Load operational data from CRMs, ERPs, and production databases into Greenplum for MPP analytics.
  • 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

Write-back of computed values

Segments, rollups, or risk flags computed in Greenplum 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 Greenplum 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 Greenplum for reporting the HR system cannot produce on its own.

What you can sync between Greenplum 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.

Greenplum objects Lever objects How this pairing syncs
External tables Reference external files for bulk load paths alongside row-level syncs. Stages Pipeline stage definitions that Opportunities move through; read to model funnel state and stage transitions in a database. External tables is specific to Greenplum and Stages to Lever — each maps to any object or custom field on the other side.
Rows Read and written by key; distribution keys determine where rows live. Feedback Interview feedback and scorecard forms attached to Opportunities; created via POST /opportunities/:id/feedback and consolidated into a warehouse for interviewer analytics. Rows is specific to Greenplum and Feedback to Lever — each maps to any object or custom field on the other side.
Databases Top-level containers that scope a sync connection. Interviews Scheduled interview panel events with times and interviewers; read for scheduling reporting and time-to-hire metrics, and creatable via the panels endpoint. Databases is specific to Greenplum and Interviews to Lever — each maps to any object or custom field on the other side.
Schemas Namespace tables and control which objects a sync can see. 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. Schemas is specific to Greenplum and Notes and Contacts to Lever — each maps to any object or custom field on the other side.
Tables Heap or append-optimized tables mapped directly to sync targets. 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. Tables is specific to Greenplum and Opportunities to Lever — each maps to any object or custom field on the other side.
Partitions Large tables are commonly partitioned by date, which shapes incremental reads. 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. Partitions is specific to Greenplum and Postings to Lever — each maps to any object or custom field on the other side.

How changes propagate between Greenplum 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.

Greenplum Lever Interval-based propagation

DetectionStacksync polls Greenplum for changes on an incremental schedule, reading only records changed since the previous pass. Polling with timestamp or key-based cursors.

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

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

Rate-limit considerations

  • Greenplum: Bounded by cluster resources and concurrency settings rather than an API quota.
  • 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 Greenplum ⇄ Lever

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Greenplum 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 Greenplum or Lever record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Greenplum and Lever connectors work

Greenplum

Integration surface
PostgreSQL wire protocol (libpq), plus JDBC/ODBC drivers
Authentication
Database credentials
Change detection
Polling with timestamp or key-based cursors; Greenplum does not expose logical-decoding CDC
Capabilities
read · write
Rate limits
Bounded by cluster resources and concurrency settings rather than an API quota.

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

    Choose tables

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

Greenplum 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
→ 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:

Related integrations

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