Data Platform Architect - EY GDS
Tasks
- Analyze current state AI platform architectures
- Define and implement AI platform KPIs
- Define data modeling and data management standards
- Define north star target transition platform architectures
- Design AI platforms on Azure AWS or GCP
- Design ETL/ELT pipelines
- Design data warehouse data lake and lakehouse
- Embed responsible AI compliance and ethics
- Enable generative AI solutions
- Enable machine learning deep learning workloads
- Ensure data governance, security, and privacy compliance
- Evaluate compute storage networking availability scalability fault tolerance disaster recovery
- Implement LLM systems
- Implement RAG architecture
- Implement batch near real time real time data processing
- Implement data cataloging and lineage
- Implement master data management
- Improve metadata and data quality frameworks
- Provide architecture guidance best practices
- Support production ready scalable governed AI platforms
Perks/Benefits
Skills/Tech-stack
AWS | Azure | Cloud Architecture | Data Cataloging | Data Governance | Data Lake | Data Lineage | Data Management | Data Modeling | Data Quality | Data Warehouse | Deep learning | Disaster Recovery | ELT | ETL | GCP | Generative AI | LLM | Lakehouse | Machine Learning | Master Data | Master Data Management | Metadata Management | Near-real-time | Near-real-time Processing | Python | RAG | Real Time | Real-time Processing | SQL | Time processing
Education
N/A
Regions
Countries
States
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