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Data warehouse ⇄ Human resources

AWS S3 to Greenhouse integration — real-time, two-way sync

Keep AWS S3 and Greenhouse 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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Why teams connect AWS S3 and Greenhouse

Land the people and organization records from Greenhouse in AWS S3 as live tables for workforce reporting, without extract jobs, and write computed results back where Greenhouse 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 Greenhouse is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in AWS S3 next to everything else the company measures.

Stacksync syncs Candidates, Applications, Jobs, Offers from Greenhouse into tables in AWS S3 continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in AWS S3, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Greenhouse 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 Ingest partner or vendor file drops (CSV, JSON, Parquet) from a bucket into a database or CRM as records.
  • 02 Export synced operational data to S3 as files feeding a data lake or downstream batch jobs.
  • 03 Write enriched or sourced Candidates from external tools into Greenhouse and keep contact fields refreshed as data changes.
  • 04 Stream Jobs, Departments, and Offices into a reporting database for recruiting funnel and time-to-fill dashboards.

Common sync patterns

Headcount and cost joined with everything else

Analysts combine Greenhouse's workforce records with finance, product, or operational data already in AWS S3 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.

Queryable history for planning and audit

A continuously synced copy in AWS S3 gives you a durable, queryable record of how Greenhouse's records change over time, for headcount planning and audit questions.

What you can sync between AWS S3 and Greenhouse

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.

AWS S3 objects Greenhouse objects How this pairing syncs
Prefixes Key-name paths used to partition synced datasets, since S3 has no real directories. Applications Links a Candidate to a Job; carries current stage, status, and source. Movable, rejectable, and hireable through Harvest write calls. Prefixes is specific to AWS S3 and Applications to Greenhouse — each maps to any object or custom field on the other side.
Object Metadata System and user-defined metadata read alongside object contents. Jobs Requisitions with openings, hiring team, departments, and offices; created and patched via Harvest, read out for funnel and time-to-fill reporting. Object Metadata is specific to AWS S3 and Jobs to Greenhouse — each maps to any object or custom field on the other side.
Object Versions Prior copies retained when versioning is enabled, relevant for reprocessing. Offers Offer records tied to an Application with status and custom offer fields; readable and patchable, commonly synced to HRIS on hire. Object Versions is specific to AWS S3 and Offers to Greenhouse — each maps to any object or custom field on the other side.
Event Notifications Notifications on object creation or deletion that trigger incremental processing. Scorecards Interviewer feedback and ratings tied to interviews; read-only in Harvest, exported to a warehouse for interview analytics. Event Notifications is specific to AWS S3 and Scorecards to Greenhouse — each maps to any object or custom field on the other side.
Access Points Scoped network endpoints used to grant a sync narrow access to a bucket. Scheduled Interviews Interview events with interviewers, times, and rooms; full create/update/delete support for calendar and reporting syncs. Access Points is specific to AWS S3 and Scheduled Interviews to Greenhouse — each maps to any object or custom field on the other side.
Multipart Uploads The mechanism used to write large export files reliably. Users Greenhouse users (recruiters, hiring managers); read and written, and referenced by the On-Behalf-Of header on every write. Multipart Uploads is specific to AWS S3 and Users to Greenhouse — each maps to any object or custom field on the other side.

How changes propagate between AWS S3 and Greenhouse

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.

AWS S3 Greenhouse Sub-second propagation

DetectionAWS S3 notifies Stacksync of record changes through webhook events. S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge.

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

Greenhouse AWS S3 Sub-second propagation

DetectionGreenhouse notifies Stacksync of record changes through webhook events. HMAC-SHA256 signed webhooks for candidate, application, job, and interview events, plus polling list endpoints with created_after / updated_after /.

DeliveryEach detected change is written to AWS S3 through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • AWS S3: Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes.
  • Greenhouse: Harvest enforces a per-integration limit over a rolling 10-second window (X-RateLimit-Limit, commonly 50 requests / 10s for approved integrations); responses carry X-RateLimit-Remaining and, on a 429, X-RateLimit-Reset and Retry-After.
What ships with AWS S3 ⇄ Greenhouse

Connect AWS S3 and Greenhouse for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS S3–Greenhouse connection.

Real-time

Two-way sync

Changes in AWS S3 or Greenhouse instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS S3 or Greenhouse 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 AWS S3 or Greenhouse record.

Observability

Monitoring

Track your AWS S3 ⇄ Greenhouse sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS S3 and Greenhouse.

How the AWS S3 and Greenhouse connectors work

AWS S3

Integration surface
REST API (the S3 API), accessed directly or through AWS SDKs
Authentication
AWS IAM credentials with SigV4 signing; commonly a role scoped to specific buckets and prefixes
Change detection
S3 Event Notifications on object create/delete delivered to SQS, SNS, Lambda, or EventBridge; list-based polling as a fallback
Capabilities
read · write · webhooks
Rate limits
Request throughput scales per prefix; sustained high-volume workloads should spread keys across prefixes

Greenhouse

Integration surface
Harvest REST API (plus read-only Job Board API and the Ingestion API for bulk candidate import)
Authentication
HTTP Basic Auth with a Harvest API key (key as username, blank password, colon appended then Base64-encoded); write calls require an On-Behalf-Of header naming the Greenhouse user
Change detection
HMAC-SHA256 signed webhooks for candidate, application, job, and interview events, plus polling list endpoints with created_after / updated_after / last_activity_after filters
Capabilities
read · write · webhooks
Rate limits
Harvest enforces a per-integration limit over a rolling 10-second window (X-RateLimit-Limit, commonly 50 requests / 10s for approved integrations); responses carry X-RateLimit-Remaining and, on a 429, X-RateLimit-Reset and Retry-After.
Greenhouse setup guide
How it works

How to connect AWS S3 to Greenhouse — 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 AWS S3 and Greenhouse 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
    AWS S3 connected
    Greenhouse connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the AWS S3 and Greenhouse 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 · AWS S3 ⇄ Greenhouse
    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
    AWS S3 Greenhouse
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

AWS S3 and Greenhouse 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

Every pair below is a real-time, two-way sync. Search all 543 integrations available for AWS S3 and Greenhouse.

Popular · 8 of 543
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