Data Engineer - Hybrid, Cloud Migration & BigQuery

Kaleidoscope Innovation, Inc.

Charlotte (NC)

Hybrid

USD 100,000 - 130,000

Full time

9 days ago

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Job summary

Kaleidoscope Innovation, Inc. in Charlotte, NC is seeking a Data Engineer to help modernize enterprise data platforms and support cloud migration initiatives.

This hands-on role focuses on designing and building scalable data pipelines and optimizing data workflows as legacy environments move to Google Cloud. You'll collaborate with architects, developers and analysts to deliver reliable data solutions, write optimized SQL, and ensure data quality and performance across systems.

Qualifications

  • 5+ years of Data Engineering/ETL experience.
  • Hands-on with GCP, BigQuery, Ab Initio, or Teradata.
  • Strong SQL development and data warehousing knowledge.
  • Experience designing enterprise data pipelines and data quality

Responsibilities

  • Design, develop, and maintain enterprise ETL/data integration pipelines.
  • Build and optimize data solutions using GCP, BigQuery, Ab Initio, Teradata.
  • Support migration of legacy data platforms to Google Cloud.
  • Develop and optimize SQL queries, data models, and data warehouse solutions.
  • Ensure data quality, performance, and reliability across enterprise systems.
  • Collaborate with architects, developers, analysts, and business stakeholders to deliver scalable data solutions.
  • Troubleshoot and resolve data integration and performance issues.

Skills

Data engineering
SQL
ETL development
Data modeling
Communication

Tools

GCP
BigQuery
Ab Initio
Teradata

Job description

Kaleidoscope Innovation, Inc. in Charlotte, NC is seeking a Data Engineer to help modernize enterprise data platforms and support cloud migration initiatives.

This hands-on role focuses on designing and building scalable data pipelines and optimizing data workflows as legacy environments move to Google Cloud. You'll collaborate with architects, developers and analysts to deliver reliable data solutions, write optimized SQL, and ensure data quality and performance across systems.

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