ETL Engineer - Scalable Data Pipelines & QA/QC (Hybrid)

ConsultNet Technology Services and Solutions; Salt Lake City (UT); Hybrid; USD 62,000 - 76,000; Full time

Job summary

ConsultNet Technology Services and Solutions seeks an experienced ETL Engineer to design, develop, and optimize data ingestion, transformation, and integration processes. You will work with large datasets to improve loading, linking, and standardization while ensuring data quality through QA/QC practices.

The ideal candidate has strong hands‑on experience building and supporting production ETL solutions and can develop reliable, scalable data pipelines in a collaborative enterprise environment.

Qualifications

• 3–5 years of hands‑on experience building and supporting production ETL solutions.
• Experience designing and developing data ingestion, transformation, and integration pipelines.
• Experience importing, exporting, and processing large datasets.
• Strong understanding of data transformation, standardization, and data quality practices.
• Experience developing and optimizing data loading and data linking workflows.
• Experience implementing QA/QC processes for data pipelines and integration solutions.
• Ability to troubleshoot and resolve data integration and quality issues.
• Proven ability to build reliable and scalable production data pipelines.

Responsibilities

• Design, develop, and optimize ETL pipelines for enterprise data initiatives.
• Work with large datasets to improve data loading, linking, and standardization processes.
• Ensure data quality through rigorous QA/QC practices and testing.
• Collaborate with data engineers, analysts, researchers, and other technical teams to support data initiatives.

Skills

ETL development

Data ingestion

Data transformation

Data quality

Data loading

QA/QC

Production pipelines

Troubleshooting

Job description

ConsultNet Technology Services and Solutions seeks an experienced ETL Engineer to design, develop, and optimize data ingestion, transformation, and integration processes. You will work with large datasets to improve loading, linking, and standardization while ensuring data quality through QA/QC practices.

The ideal candidate has strong hands‑on experience building and supporting production ETL solutions and can develop reliable, scalable data pipelines in a collaborative enterprise environment.