Job Description :
- Designing, building, and operating scalable on-premises or cloud data architecture
- Analyzing business requirements and translating them into technical specifications
- Design, develop, and implement data engineering solutions using Databricks on cloud platforms (AWS, Azure)
- Design, develop, and maintain scalable data pipelines and ETL processes
- Collaborate with data scientists and analysts to understand data requirements and implement solutions
that support analytics and machine learning initiatives.
Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectivenessImplement data governance and security best practices to ensure compliance and data integrityTroubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoringStay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.Qualifications :
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.Overall 6- 10 years of prior experience in data engineering, with a focus on designing and building data pipelines5+ years experience in Databricks and Spark in at least two end-to-end data engineering implementationsComprehensive understanding of the Databricks products and ecosystemStrong programming skills in languages such as Python, Scala, or SQL.Experience with data modeling, ETL processes, and data warehousing concepts.Familiarity with containerization technologies orchestration tools is a plus.(ref : hirist.tech)