AI Data Engineer for Cloud Platforms
1 day ago
We are expanding our team of experts in solution architecture and engineering to support the growth of a Generative AI MVP for frontline banking scenarios. This strategic project focuses on enhancing and expanding our platform, leveraging Databricks and AWS platforms.
Key Responsibilities:
Solution Architecture and Engineering:
- Design and implement scalable and efficient data engineering pipelines in Databricks.
- Architect data solutions that align with AWS cloud infrastructure and integrate with Generative AI models like Llama 3.
Data Migration:
- Migrate large-scale transactional datasets (50k+ rows and columns) from SQL on-premises to Databricks and AWS S3/Redshift.
- Ensure data quality, integrity, and security during migration.
Data Integration & Optimization:
- Build and optimize data pipelines for various use cases, including transactional data for cards and business banking.
- Collaborate with data scientists and Generative AI engineers to integrate structured and unstructured data for AI-driven solutions.
Performance Tuning:
- Fine-tune the performance of data pipelines and models for real-time or batch processing.
- Optimize Databricks clusters for cost efficiency and speed.
Collaboration:
- Work closely with the Generative AI engineering team to expand the MVP into additional scenarios for frontline bankers.
- Partner with stakeholders to gather requirements and provide insights to shape data solutions.
Estimated Salary: $140,000 - $160,000 per year.
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