You will be a key member of our Data Engineering team, focused on designing, developing, and maintaining robust data solutions on on-premise environments. You will work closely with internal teams and client stakeholders to build and optimize data pipelines and analytical tools using Python, PySpark, SQL, and Hadoop ecosystem technologies. This role requires deep hands-on experience with big data technologies in traditional data center environments (non-cloud).
What you ll be doing
Design, build, and maintain on-premise data pipelines to ingest, process, and transform large volumes of data from multiple sources into data warehouses and data lakes
Develop and optimize PySpark and SQL jobs for high-performance batch and real-time data processing
Ensure the scalability, reliability, and performance of data infrastructure in an on-premise setup
Collaborate with data scientists, analysts, and business teams to translate their data requirements into technical solutions
Troubleshoot and resolve issues in data pipelines and data processing workflows
Monitor, tune, and improve Hadoop clusters and data jobs for cost and resource efficiency
Stay current with on-premise big data technology trends and suggest enhancements to improve data engineering capabilities
Bachelor s degree in Computer Science, Software Engineering, or a related field
6+ years of experience in data engineering or a related domain
Strong programming skills in Python (with experience in PySpa
Keyskills: Analytical Hadoop Cloud Data processing sqoop big data Data warehousing SQL Python
BLEND360 is an award-winning, new breed Data Science Solutions Company focused on powering exceptional results to our Fortune 500/1000 clients and other organizations. We are a hyper growth company - born at the intersection of advanced analytics, data and technology. ...