Data Pipeline Development & Infrastructure
- Design, build, and maintain scalable data pipelines
- Develop real-time and batch data processing frameworks for structured and unstructured data.
- Implement ETL/ELT workflows to ingest data from various sources, ensuring high availability and performance.
- Optimize data storage and retrieval of data in (near) real time and batch processes
- Ensure cost-efficient and high-performance data infrastructure that scales with business needs.
Data Solutions & AI-Driven Applications
- develop data pipelines for ML recommenders, search functionality, and AI-enhanced features.
- Develop and maintain data models, APIs, and integrations to support analytics and customer applications.
- Support eCommerce-related data solutions, including product recommendations, customer segmentation, and personalization models.
Collaboration & Continuous Improvement
- Work closely with Data Architects, Analysts, and Product Teams to understand data requirements and deliver best-in-class solutions.
- Monitor and troubleshoot performance issues, ensuring high availability and efficiency of data pipelines.
- Continuously optimize cost, performance, and scalability of data engineering solutions.