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# Data Engineering IT Professional

- **Company:** Global Channel Management, Incorporated
- **Location:** Raleigh, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Adobe InDesign, Amazon Web Services, Cloud Computing, Cloud Database, Information Systems, Databases, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Mart, Data Warehousing, IBM InfoSphere DataStage, Dimensional Modeling, Python (Programming Language), Microsoft SQL Server, Operational Data Store, Oracle (Applications), Performance Tuning, SAS (Software), SQL Databases, Teradata SQL, Scripting, Informatica Powercenter, Netezza, Snowflake, Informatica Cloud, Sap Business Objects, Gitlab, Data Lakes, Information Technology, AWS Glue, Google Bigquery, Data Management, Physical Data Models, Software Version Control, Data Pipelines, Amazon Redshift
- **Published:** November 13, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineering-it-professional-raleigh-nc--f0a573a4-7c1d-414b-8719-70c31b22845b

## About the Role

Information Technology & Information Systems, Information Technology & Information Systems, Data Management, Database Extract Transform and Load (ETL), SAP BusinessObjects, Cloud Computing, IBM Product Family, Informatica, Business Services, Amazon Web Services (AWS), Data Engineering IT Professional needs 5 years experience
Data Engineering IT Professional requires:
Gitlab version control and CI/CD
Expertise in design and development of complex data pipelines
Solutions using any industry leading ETL tools such as SAP Business Objects Data Services (BODS), Informatica Cloud Data Integration Services (IICS), IBM Data Stage.
Experience of ELT tools such as DBT, Fivetran, and AWS Glue
Expert in SQL - development experience in at least one scripting language (Python etc.), adept in tracing and resolving data integrity issues.
Strong knowledge of data architecture, data design patterns, modeling, and cloud data solutions (Snowflake, AWS Redshift, Google BigQuery).
Data Model: Expertise in Logical and Physical Data Model using Relational or Dimensional Modeling practices, high volume ETL/ELT processes.
Performance tuning of data pipelines and DB Objects to deliver optimal performance.
SAS ETL skills for current SAS script maintenance and minor enhancements, but should re ready to also use other ETL tools listed below for future state
Experience in designing and building Data Warehouse and Data lakes. Good knowledge of data warehouse principles, and concepts.
Technical expertise working in large scale Data Warehousing applications and databases such as Oracle, Netezza, Teradata, and SQL Server.
Experience with public cloud-based data platforms especially Snowflake and AWS.

Data Engineering IT Professional duties:
Design, build, and maintain data pipelines that supports data integrations for Enterprise Data Warehouse, Operational Data Store or Data Marts etc