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Robert Half
Data Engineer
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Job Description
We are seeking an experienced Data Engineer to architect, build, and optimize scalable data pipelines and cloud-based data platforms that support advanced analytics, reporting, and business intelligence initiatives.
ResponsibilitiesDesign, develop, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading structured and semi-structured data.
Build and manage scalable data pipelines using Python and SQL across cloud and warehouse environments.
Optimize data storage, query performance, and overall efficiency within modern data warehouse platforms.
Develop and maintain data models that support downstream analytics, reporting, and operational use cases.
Collaborate with business stakeholders, analysts, and engineering teams to define data requirements and translate them into technical solutions.
Implement and support data quality checks, governance standards, and monitoring processes to ensure data reliability and integrity.
Troubleshoot pipeline failures, performance bottlenecks, and data consistency issues across the data ecosystem.
Contribute to best practices in data architecture, orchestration, documentation, and deployment.
ResponsibilitiesDesign, develop, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading structured and semi-structured data.
Build and manage scalable data pipelines using Python and SQL across cloud and warehouse environments.
Optimize data storage, query performance, and overall efficiency within modern data warehouse platforms.
Develop and maintain data models that support downstream analytics, reporting, and operational use cases.
Collaborate with business stakeholders, analysts, and engineering teams to define data requirements and translate them into technical solutions.
Implement and support data quality checks, governance standards, and monitoring processes to ensure data reliability and integrity.
Troubleshoot pipeline failures, performance bottlenecks, and data consistency issues across the data ecosystem.
Contribute to best practices in data architecture, orchestration, documentation, and deployment.