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6 days ago
The ideal candidate will design, develop, and maintain scalable data pipelines to ingest, transform, and integrate data from various sources. They will also implement real-time data streaming and batch processing solutions to support diverse business needs.
Key Responsibilities:- Data Pipeline Development: Develop efficient ETL/ELT pipelines that enable seamless data flow and integration.
- Data Streaming and Processing: Implement cutting-edge real-time data streaming and batch processing solutions to cater to dynamic business requirements.
- Data Storage Solutions: Design and optimize data storage solutions, including data lakes, data warehouses, and databases.
- Data System Optimization: Ensure high-performance data systems and pipelines that meet scalability and security standards.
- Data Cleansing and Preparation: Effectively clean, transform, and prepare raw data for analytics and machine learning applications.
- Collaboration with Data Teams: Collaborate closely with Data Scientists and Analysts to define data requirements and deliver innovative solutions.
- Performance Monitoring: Monitor the performance and reliability of data pipelines and systems, implementing improvements as needed.
- Troubleshooting: Troubleshoot and resolve complex data-related issues promptly.
- Data Quality Assurance: Establish and enforce robust data quality checks, validation processes, and monitoring mechanisms.
- Data Governance: Work with Data Governance teams to ensure data complies with organizational standards and policies.
- Cross-Functional Collaboration: Foster strong relationships with cross-functional teams to understand requirements and deliver effective data solutions.
- Technical Expertise: Provide expert guidance on data engineering best practices and emerging technologies.
- Technology Evaluation: Stay updated on industry trends and evaluate technologies to enhance data engineering capabilities.
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