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Job Description

Experis is seeking a Senior Azure Data Engineer to support a business-critical HR data integration initiative, connecting SAP SuccessFactors to an Azure Databricks analytics platform. This contract role focuses on designing and optimizing end-to-end ETL/ELT pipelines for HR and organizational datasets, with API-based ingestion from SuccessFactors into a modern Azure data platform.

Role overview

In this position, you will build and maintain scalable data pipelines on Microsoft Azure that extract HR and organizational data from SAP SuccessFactors, orchestrate ingestion with Azure Data Factory, and process transformations using Databricks with PySpark and advanced SQL. You will also manage enterprise datasets in ADLS and implement strategies for incremental and full-load extraction to support data integrity and performance.

Responsibilities

  • Design, build, and maintain scalable, high-performance data pipelines within Microsoft Azure for enterprise data platform initiatives.
  • Develop automated ingestion pipelines that extract HR, organizational, compensation, job, recruiting, and performance data from SAP SuccessFactors into Azure Databricks.
  • Use SAP SuccessFactors OData APIs, Compound Employee APIs, and related integration mechanisms, coordinating with Azure Data Factory (ADF) for orchestration, scheduling, and pipeline management.
  • Create data processing and transformation solutions using Azure Databricks, PySpark, and advanced SQL.
  • Manage data within Azure Data Lake Storage (ADLS) and Azure-based data platforms, including data modeling, stored procedures, and incremental and full-load extraction approaches.
  • Implement robust data validation, reconciliation, error-handling, and performance tuning across integration workflows.
  • Collaborate with HR business analysts and technical stakeholders to translate complex data requirements into production-ready engineering solutions.

Requirements

  • Proven experience as an Azure Data Engineer with expertise in Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), and complex SQL.
  • Hands-on experience extracting and processing data from SAP SuccessFactors using OData APIs, Compound Employee APIs, or other API-based integration patterns into Databricks and Azure architectures.
  • Strong proficiency with PySpark and Python for data transformation and distributed processing in Databricks.
  • Background designing incremental load and delta lake strategies as well as full-load extraction strategies to ensure data integrity and scalability.
  • Excellent communication skills to engage with technical architects, data engineers, and business stakeholders.

Technologies

  • Microsoft Azure, Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS)
  • SQL, PySpark, Python
  • SAP SuccessFactors APIs, OData APIs, Compound Employee APIs
  • Delta Lake, incremental/full-load extraction strategies, ETL/ELT pipelines
  • Stored procedures

Location and engagement

  • Location: Charlotte, NC (hybrid)
  • Job type: Contract
  • Rate: USD 55 - 65 per hour
  • Initial contract term: Running through March 2027 with strong potential for multi-year extensions

Benefits

  • Medical and Prescription Drug Plans
  • Dental Plan
  • Vision Plan
  • Health Savings Account
  • Health Flexible Spending Account
  • Dependent Care Flexible Spending Account
  • Supplemental Life Insurance
  • Short Term and Long Term Disability Insurance
  • Business Travel Insurance
  • 401(k), Plus Match
  • Weekly Pay

Employment terms

  • W2 only: STRICTLY W2 (no C2C, no third-party agencies, and no referrals)
  • After waiting period completion: Consultants are eligible for the benefits listed above

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