Data Engineer for Supply chain Team

Contract role in Seattle, WA (Onsite) with Capgemini, focused on building and optimizing large-scale data pipelines and data platforms in Azure. This position supports both batch and real-time workloads, using PySpark, distributed processing, and orchestration tools to keep data systems reliable and performant.

What you’ll work on

The Data Engineer will design, build, and continuously improve data pipelines and ingestion frameworks that can scale. You’ll develop batch and real-time processing solutions with Apache Spark / PySpark, and deliver Azure-based data engineering implementations that support large distributed datasets.

• Design, develop, and maintain scalable data pipelines and data ingestion frameworks
• Build batch and real-time data processing solutions using Spark/PySpark
• Develop and optimize Azure-based data engineering solutions
• Implement and support orchestration workflows using ADF and/or Airflow
• Tune and optimize queries across large-scale distributed datasets
• Design denormalized data models for big data environments
• Perform root cause analysis and implement permanent resolutions for data and process issues
• Create and maintain technical documentation for systems and projects

Key skills and qualifications

• PySpark / Apache Spark
• Azure Data Engineering
• ADF or Airflow
• SQL & Data Modeling

Tools and technologies

• Airflow, ADF
• Apache Spark, Spark/PySpark, PySpark
• SQL
• Azure Data Engineering

Compensation and benefits

Pay range: $34.88/hour - $54.50/hour. Job type: Contract.

• Medical
• Dental
• Vision
• Retirement benefits