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2 results for Engineer in Charlotte, NC

Data Engineer
  • Charlotte, NC
  • onsite
  • Temporary / Contract
  • 55 - 65 USD / Hourly
  • <p>We are currently seeking a Data Engineer for a contract opportunity supporting a growing data and analytics organization. This role is focused on building and maintaining modern cloud-based data infrastructure, including scalable ELT pipelines, Snowflake data solutions, and automated data workflows.</p><p>This is a hands-on engineering role where you will design, develop, and support end-to-end data systems that enable reliable reporting, analytics, and business decision-making.</p><p><strong>Key Responsibilities:</strong></p><ul><li>Design, build, and maintain scalable ELT/ETL data pipelines and workflows</li><li>Develop and optimize Snowflake-based data warehouse solutions</li><li>Build and maintain data models and transformation logic to support analytics and reporting</li><li>Write efficient and high-quality Python and SQL code to support data engineering processes</li><li>Develop reusable data engineering frameworks and backend data services</li><li>Implement and maintain CI/CD pipelines using GitHub and related tooling</li><li>Build automated testing frameworks to ensure data quality and reliability</li><li>Create reporting and visualization solutions using tools such as Power BI</li><li>Monitor production data systems and resolve performance or reliability issues</li><li>Support continuous improvement of data architecture, processes, and standards</li></ul>
  • 2026-04-14T00:00:00Z
Data Engineer
  • Charlotte, NC
  • remote
  • Permanent / Full Time
  • 0 - 0 USD / Yearly
  • <ul><li>Design, develop, and optimize data pipelines using Azure Data Services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse).</li><li>Build and maintain scalable ETL/ELT workflows using Databricks (Spark, PySpark, Delta Lake).</li><li>Implement and manage data orchestration and dependency management using Dagster or similar tools.</li><li>Partner with analytics, data science, and product teams to ensure reliable, high-quality data availability.</li><li>Optimize data models and storage strategies for performance, scalability, and cost efficiency.</li><li>Ensure data quality, observability, and reliability through monitoring, logging, and automated validation.</li><li>Support CI/CD pipelines and infrastructure-as-code practices for data platforms.</li><li>Enforce data security, governance, and compliance best practices within Azure.</li></ul>
  • 2026-04-22T00:00:00Z