Ohio Data Engineer: Scalable ETL/ELT & Data Lakes
US staffing Inc
Get more replies from employers
Send a job-specific resume in minutes.
Job summary
US staffing Inc is looking for a skilled Data Engineer located in the United States, Kentucky. The role is focused on building and maintaining data pipelines and analytics platforms to support business requirements.
The ideal candidate will have over 6 years of experience and be proficient in Python, Apache Spark, and Azure Data Factory. This position demands strong independence to deliver scalable, production-grade solutions.
Qualifications
- 6+ years of hands-on experience building and maintaining data pipelines.
- Experience with Python, Apache Spark, and Azure Data Factory.
- Ability to translate business requirements into data solutions.
Responsibilities
- Own end-to-end data engineering deliverables independently.
- Design and build scalable ETL/ELT pipelines.
- Maintain centralized data lake using Microsoft Fabric/OneLake.
Job description
US staffing Inc is looking for a skilled Data Engineer located in the United States, Kentucky. The role is focused on building and maintaining data pipelines and analytics platforms to support business requirements.
The ideal candidate will have over 6 years of experience and be proficient in Python, Apache Spark, and Azure Data Factory. This position demands strong independence to deliver scalable, production-grade solutions.
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
