Georgia IT Inc
Data Engineer in Chicago, IL (onsite)
Georgia IT Inc, Chicago, Illinois, United States, 60290
Job Title: Data Engineer
Location: Chicago, IL (onsite)
Duration: 12 Months (Possible Extension)
Job ID: 24-31812
US Citizens, GC holders preferred, NO third party corp to corp accepted for this job
Key Responsibilities
Design & Development: Develop and optimize scalable, reliable, and secure data pipelines and platforms using Azure Data Services. Data Integration: Integrate data from various sources, ensuring high data quality and availability for analysis. Collaboration: Work closely with cross-functional teams, including Data Scientists, Analysts, and DevOps, to understand data requirements and deliver solutions. utomation: Leverage Python 3.x to automate data workflows and ensure efficient handling of large datasets. Version Control: Use Git/GitHub for version control, collaboration, and deployment of data solutions. WS Exposure: Apply knowledge of AWS services for hybrid cloud environments and data migrations when needed. Performance Monitoring: Monitor, troubleshoot, and optimize data systems for performance and reliability Required Qualifications
Proficiency in Python 3.x for data engineering tasks and automation. Hands-on experience with Azure Data Services, such as Azure Data Factory, Azure Databricks, and Azure SQL. Familiarity with AWS services like S3, Lambda, or Redshift is a plus.
US Citizens, GC holders preferred, NO third party corp to corp accepted for this job
Key Responsibilities
Design & Development: Develop and optimize scalable, reliable, and secure data pipelines and platforms using Azure Data Services. Data Integration: Integrate data from various sources, ensuring high data quality and availability for analysis. Collaboration: Work closely with cross-functional teams, including Data Scientists, Analysts, and DevOps, to understand data requirements and deliver solutions. utomation: Leverage Python 3.x to automate data workflows and ensure efficient handling of large datasets. Version Control: Use Git/GitHub for version control, collaboration, and deployment of data solutions. WS Exposure: Apply knowledge of AWS services for hybrid cloud environments and data migrations when needed. Performance Monitoring: Monitor, troubleshoot, and optimize data systems for performance and reliability Required Qualifications
Proficiency in Python 3.x for data engineering tasks and automation. Hands-on experience with Azure Data Services, such as Azure Data Factory, Azure Databricks, and Azure SQL. Familiarity with AWS services like S3, Lambda, or Redshift is a plus.