Enterprise Data Engineer: Build Reliable Data Solutions

Kforce Technology Staffing

New York (NY)

Hybrid

USD 120,000 - 160,000

Full time

6 days ago
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Job summary

Kforce Technology Staffing is seeking a Data Engineer to join a hybrid team across Dallas, TX, Raleigh, NC, or Princeton, NJ. This role focuses on developing reliable data solutions within an existing enterprise platform and understanding the business meaning of data to build scalable, maintainable systems.

You will design and optimize data workflows, ensure data quality, and work with stakeholders to translate requirements into technical implementations.

Qualifications

  • Experience building enterprise data solutions.
  • Experience with large/complex datasets.
  • Strong SQL and data troubleshooting capabilities.
  • Ability to understand the business context behind data.
  • Ability to collaborate across technical and business teams.

Responsibilities

  • Design, develop, test, and maintain enterprise data solutions.
  • Build and enhance data processing workflows for large datasets.
  • Translate business requirements into technical implementations.
  • Analyze source and target data for accuracy, completeness, and consistency.
  • Investigate data issues and support root-cause analysis.
  • Develop validation and reconciliation processes for critical data.
  • Improve scalability, reliability, and performance of data processes.
  • Collaborate with Oracle developers, leads, and stakeholders.
  • Participate in code reviews, testing, and documentation.
  • Enhance and redesign components within an existing platform.

Skills

SQL
Data analysis
Problem solving
Communication

Tools

Oracle

Job description

Kforce Technology Staffing is seeking a Data Engineer to join a hybrid team across Dallas, TX, Raleigh, NC, or Princeton, NJ. This role focuses on developing reliable data solutions within an existing enterprise platform and understanding the business meaning of data to build scalable, maintainable systems.

You will design and optimize data workflows, ensure data quality, and work with stakeholders to translate requirements into technical implementations.

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