EEIntegration Data Engineer

Pune - India

Monthly Salary: Not Disclosed

Posted on: 3 days ago

Vacancies: 1 Vacancy

Job Summary

Role	Data Engineering & ETL/ELT Developer
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Location	Pune
Experience:	2-5 Years
Number of openings	1
What awaits you/ Job Profile	Data Pipeline Development:Design build and maintain scalable data pipelines supporting batch and near-real-time data ingestion transformation and delivery across enterprise data platforms. ETL/ELT Design & Optimization:Develop and optimize ETL/ELT workflows to efficiently process structured and semi-structured data ensuring performance scalability and reliability. Data Quality & Reliability:Implement data validation monitoring and reconciliation mechanisms to ensure data accuracy consistency and availability across downstream consumers. Performance & Scalability:Analyze workloads and optimize data processing jobs storage layouts and query performance within distributed data environments. Platform Collaboration:Work closely with analytics data science platform and application teams to enable reliable data access and analytics use cases. Operational Excellence:Contribute to automation documentation and continuous improvement of data engineering processes and operational practices.
What should you bring along	Strong understanding of data engineering concepts distributed data processing and data integration patterns. Hands-on experience building and maintaining production-grade data pipelines. Solid knowledge of relational and analytical data systems. Good understanding of software development best practices and data lifecycle management.
Must have technical skill	Proven experience with SQL and Python (or equivalent programming language). Hands-on experience with ETL/ELT tools and frameworks. Strong knowledge of data modeling concepts and data warehousing principles. Experience working with cloud-based or hybrid data platforms. Ability to troubleshoot data pipeline failures and performance issues. Strong analytical and problem-solving skills.
Good to have Technical skills	Experience with streaming or event-driven data processing architectures. Exposure to cloud-native data services and modern analytics platforms. Automation and scripting experience (e.g. Python Shell). Familiarity with data governance metadata management and data quality frameworks. Experience working in cross-functional enterprise-scale environments.

Required Experience:

Senior IC

RoleData Engineering & ETL/ELT DeveloperVisit our websiteto know more.Follow us onLinkedInIInstagramIFacebookIXfor the exciting updates.LocationPuneExperience:2-5 YearsNumber of openings1What awaits you/ Job ProfileData Pipeline Development:Design build and maintainscalable data pipelines supporting...

Role	Data Engineering & ETL/ELT Developer
Visit our websiteto know more. Follow us onLinkedInI InstagramI FacebookI Xfor the exciting updates.

Location	Pune
Experience:	2-5 Years
Number of openings	1
What awaits you/ Job Profile	Data Pipeline Development:Design build and maintain scalable data pipelines supporting batch and near-real-time data ingestion transformation and delivery across enterprise data platforms. ETL/ELT Design & Optimization:Develop and optimize ETL/ELT workflows to efficiently process structured and semi-structured data ensuring performance scalability and reliability. Data Quality & Reliability:Implement data validation monitoring and reconciliation mechanisms to ensure data accuracy consistency and availability across downstream consumers. Performance & Scalability:Analyze workloads and optimize data processing jobs storage layouts and query performance within distributed data environments. Platform Collaboration:Work closely with analytics data science platform and application teams to enable reliable data access and analytics use cases. Operational Excellence:Contribute to automation documentation and continuous improvement of data engineering processes and operational practices.
What should you bring along	Strong understanding of data engineering concepts distributed data processing and data integration patterns. Hands-on experience building and maintaining production-grade data pipelines. Solid knowledge of relational and analytical data systems. Good understanding of software development best practices and data lifecycle management.
Must have technical skill	Proven experience with SQL and Python (or equivalent programming language). Hands-on experience with ETL/ELT tools and frameworks. Strong knowledge of data modeling concepts and data warehousing principles. Experience working with cloud-based or hybrid data platforms. Ability to troubleshoot data pipeline failures and performance issues. Strong analytical and problem-solving skills.
Good to have Technical skills	Experience with streaming or event-driven data processing architectures. Exposure to cloud-native data services and modern analytics platforms. Automation and scripting experience (e.g. Python Shell). Familiarity with data governance metadata management and data quality frameworks. Experience working in cross-functional enterprise-scale environments.