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Data warehouse ⇄ Human resources

Databricks to Paylocity integration — real-time, two-way sync

Keep Databricks and Paylocity 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 Databricks and Paylocity

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

Stacksync syncs Local and State Taxes, Direct Deposit, Pay Statements, Company Codes from Paylocity into tables in Databricks continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Databricks, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Paylocity 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 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
  • 02 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 03 Two-way sync of Employees between Paylocity and an HRIS or identity provider so new hires, terminations, and demographic edits flow both directions.
  • 04 Push hired candidates from an ATS into Paylocity via the Onboarding endpoint, then read Onboarding Status to confirm the record before the first payroll run.

Common sync patterns

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 Databricks gives you a durable, queryable record of how Paylocity's records change over time, for headcount planning and audit questions.

Write-back of computed values

Segments, rollups, or risk flags computed in Databricks sync back onto the matching records in Paylocity, where the HR team sees them in the system they already use.

What you can sync between Databricks and Paylocity

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.

Databricks objects Paylocity objects How this pairing syncs
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Pay Statements Read-only detailed payroll statement data — earnings, deductions, taxes, and direct deposit allocations by year, check date, or date range. Pulled for reporting, never written. Catalogs is specific to Databricks and Pay Statements to Paylocity — each maps to any object or custom field on the other side.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Company Codes Read-only reference codes and descriptions (cost centers, departments, positions) used to validate field mappings on employee writes. Schemas is specific to Databricks and Company Codes to Paylocity — each maps to any object or custom field on the other side.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Custom Fields Read-only company-specific custom fields returned by category, used to enrich the employee record downstream. Delta Tables is specific to Databricks and Custom Fields to Paylocity — each maps to any object or custom field on the other side.
Views Curated read-only projections used as sync sources for downstream tools. Employees Core HR record keyed by companyId + employeeId; two-way via Create New Employee (POST) and Update Employee (PATCH), plus Get Employee / Get All Employees for reads. Views is specific to Databricks and Employees to Paylocity — each maps to any object or custom field on the other side.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Onboarding Create Employee Onboarding pushes new-hire data into Paylocity's onboarding workflow; Get Onboarding Status reads back partner onboarding progress. Write-in for hires from an ATS. Materialized Views is specific to Databricks and Onboarding to Paylocity — each maps to any object or custom field on the other side.
Volumes Unity Catalog file storage used for staging bulk loads. Deductions (Pay Setup) Recurring deduction codes at the employee level; two-way via Upsert Deduction and Delete, with Get Deduction / Get All Deductions for reads. Volumes is specific to Databricks and Deductions (Pay Setup) to Paylocity — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Paylocity

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.

Databricks Paylocity Sub-second propagation

DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.

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

Paylocity Databricks Sub-second propagation

DetectionPaylocity notifies Stacksync of record changes through webhook events. Webhooks — Paylocity POSTs Employee New Hire, Employee Change, Termination, Payroll Processed, and Time Off Approval events to a callback URL.

DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
  • Paylocity: 25 requests per second (1,500 per minute); exceeding it returns HTTP 429. Every path is scoped to a Paylocity-assigned companyId (a company code, not a UUID).
What ships with Databricks ⇄ Paylocity

Connect Databricks and Paylocity for flexible, real-time data sync.

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

Real-time

Two-way sync

Changes in Databricks or Paylocity instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Paylocity 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 Databricks or Paylocity record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Databricks and Paylocity.

How the Databricks and Paylocity connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits

Paylocity

Integration surface
REST API (v1 and v2), JSON payloads
Authentication
OAuth 2.0 client credentials via the Paylocity Identity Provider (/IdentityServer/connect/token) with the WebLinkAPI scope; access tokens expire after one hour and API access must be enabled by Paylocity for the company
Change detection
Webhooks — Paylocity POSTs Employee New Hire, Employee Change, Termination, Payroll Processed, and Time Off Approval events to a callback URL; payloads carry only companyId and employeeId, so the receiver calls the relevant API to fetch changed values. Scheduled polling is used for objects without webhooks.
Capabilities
read · write · webhooks
Rate limits
25 requests per second (1,500 per minute); exceeding it returns HTTP 429. Every path is scoped to a Paylocity-assigned companyId (a company code, not a UUID).
How it works

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

    Choose tables

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

Databricks and Paylocity 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 550 integrations available for Databricks and Paylocity.

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