GCP Data Engineer Adobe Experience Platform (AEP)

Artech LLC

  • Atlanta, GA
  • 3 days ago
  • $55–$58 Per Hour

Highlights

We are seeking a highly experienced Senior GCP Data Engineer with strong expertise in Google Cloud data engineering, backend development, and Adobe Experience Platform (AEP) . The ideal candidate will have 8+ years of experience in ETL/ELT, data engineering, data warehousing, and building scalable data pipelines.

Numbers & Facts

LocationAtlanta, GA
Salary$55–$58 Per Hour

Description

Requisition ID: 95826-1
Title: GCP Data Engineer Adobe Experience Platform (AEP)
Location: Atlanta, GA
Duration: 6+ Months
Salary Range: $55- $58 an hour on W2 /C2C
Note:
Only for Visa-independent candidate

We are seeking a highly experienced Senior GCP Data Engineer with strong expertise in Google Cloud data engineering, backend development, and Adobe Experience Platform (AEP).

The ideal candidate will have 8+ years of experience in ETL/ELT, data engineering, data warehousing, and building scalable data pipelines. Candidates must have hands-on experience with Adobe Experience Platform (AEP) and backend data engineering.

Important: This role specifically requires AEP (Adobe Experience Platform) and backend experience. AEM (Adobe Experience Manager) experience is NOT a substitute and should not be prioritized.

Must-Have Technical Skills

  • 8+ years of experience in Data Engineering, ETL/ELT, and Data Warehousing.
  • Strong hands-on experience with Adobe Experience Platform (AEP).
  • Strong backend data engineering experience.
  • 5+ years of experience designing and developing data models and scalable data pipelines.
  • Strong expertise in Google Cloud Platform (GCP).
  • Hands-on experience with:
    • BigQuery
    • Dataflow
    • Dataproc
    • Pub/Sub
    • Google Cloud Storage
    • Cloud Composer / Apache Airflow
  • Strong SQL skills.
  • Strong programming experience with Python and/or Java.
  • Experience developing and managing Airflow/Composer DAGs.
  • Experience with CI/CD using GitHub, Jenkins, or similar tools.
  • Strong understanding of cloud-native data engineering and distributed data processing.
  • Experience designing secure, scalable, reliable, and cost-optimized data pipelines.

Roles & Responsibilities

  • Design, develop, and maintain scalable GCP data pipelines supporting analytics and data science workloads.
  • Build robust ETL/ELT pipelines using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Airflow/Composer.
  • Develop data models and data-processing solutions for large-scale enterprise datasets.
  • Integrate and work with Adobe Experience Platform (AEP) as part of enterprise data solutions.
  • Develop backend data-processing and integration components.
  • Design secure and highly available data pipelines aligned with enterprise governance, privacy, security, and data-quality standards.
  • Optimize data pipelines for performance, scalability, reliability, and cloud cost efficiency.
  • Develop and maintain Airflow/Cloud Composer DAGs for automated data workflows.
  • Write optimized SQL queries and develop data transformation logic using Python and/or Java.
  • Implement CI/CD processes using GitHub, Jenkins, and related DevOps tools.
  • Troubleshoot data pipeline failures and perform root-cause analysis.
  • Collaborate with onsite and offshore engineering teams to deliver high-quality data solutions.
  • Partner with data architects, analysts, data scientists, and business stakeholders to understand data requirements.
  • Ensure data solutions comply with enterprise security, governance, privacy, and quality standards.
  • Support continuous improvement of data engineering platforms and processes.

Preferred Qualifications

  • Retail industry experience.
  • Experience working with large-scale enterprise data platforms.
  • Experience with cloud-native architecture and distributed data processing.
  • Experience integrating Adobe Experience Platform with backend data platforms.
  • Strong understanding of data governance, data privacy, and data quality practices.

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