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Data & Analytics · Case Study

iCIMS Recruiting Data Integration into Azure Data Lake

iCIMS is a SaaS ATS without a traditional database source. MSPowerhouse designed a parent-child ADF pipeline that first searched for record IDs, then looped through detail endpoints, handled pagination, and landed raw JSON in Azure Data Lake Gen2.

Client
Confidential
Engagement
2024
Industry
Data & Analytics
Outcome
API-first SaaS extraction pattern
iCIMS Recruiting Data Integration into Azure Data Lake

The challenge

  • iCIMS could not be treated like a database source — REST/HTTP extraction only.
  • Two-step extraction needed: discover IDs, then call detail endpoints.
  • Required pagination, profile-level extraction, and scalable expansion to more objects.

Our approach

  • Designed a parent-child ADF pattern with ForEach over discovered IDs.
  • Configured REST source, authentication, pagination, and raw JSON landing.
  • Stored raw output in ADLS so downstream teams could transform without re-hitting the API.
  • Created a reusable framework for future ATS objects.

Results

Parent/Child
Pipeline orchestration
Reusable
Pattern for future ATS objects
Reduced
Manual exports and re-extraction cost

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