oracle
LEAD ASSISTANT MANAGER
EXL
Haryana, IND
Lead · 5–8 years experience
Hybrid
Discovered 2 weeks ago
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About the Role
We are seeking an experienced Lead Assistant Manager - Data Engineering to design, build, and optimize scalable data pipelines and modern data platforms. The role will support enterprise analytics, reporting, and AI/ML initiatives by ensuring reliable, secure, and high-quality data availability across the organization.
Key Skills for This Role
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Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Build and optimize data models, data warehouses, data lakes, and modern data architectures.
- Develop data ingestion, transformation, and integration processes using cloud-native technologies.
- Ensure data quality, integrity, reliability, and governance across enterprise data assets.
- Collaborate with business, analytics, and data science teams to understand and deliver data requirements.
- Implement data pipeline monitoring, troubleshooting, and performance optimization procedures.
- Support real-time and batch data processing requirements.
- Automate data workflows and deployment processes using CI/CD best practices.
- Ensure compliance with security, privacy, and organizational data standards.
- Mentor junior team members and provide technical guidance on data engineering best practices.
- Participate in architecture discussions and recommend enhancements to improve scalability and efficiency.
- - Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data. - Build and optimize data models, data warehouses, data lakes, and modern data architectures. - Develop data ingestion, transformation, and integration processes using cloud-native technologies. - Ensure data quality, integrity, reliability, and governance across enterprise data assets. - Collaborate with business, analytics, and data science teams to understand and deliver data requirements. - Implement data pipeline monitoring, troubleshooting, and performance optimization procedures. - Support real-time and batch data processing requirements. - Automate data workflows and deployment processes using CI/CD best practices. - Ensure compliance with security, privacy, and organizational data standards. - Mentor junior team members and provide technical guidance on data engineering best practices. - Participate in architecture discussions and recommend enhancements to improve scalability and efficiency.
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