Senior AI Data Analytics Engineer
Tasks
- Accelerate development with AI coding and analytics assistants
- Architect Snowflake AWS RDS AWS DynamoDB solutions
- Build retrieval-augmented generation workflows
- Build semantic search over enterprise data
- Define key business metrics with stakeholders
- Design and operationalize AI ML workflows
- Design data dictionaries semantic layers and data catalogs
- Design scalable data models
- Establish data quality testing monitoring and documentation
- Integrate data from AWS S3
- Mentor engineers through design reviews pairing and code review
- Own data and AI architecture roadmap
- Provide AI powered self service insights
- Set data engineering standards and best practices
- Set technical direction for payment performance analytics
- Support reconciliation and audit readiness
- Translate business strategy into data and AI solutions
- Validate responsible AI practices for bias hallucination and privacy
Perks/Benefits
- N/A
Skills/Tech-stack
Amazon DynamoDB | Amazon RDS | Amazon S3 | Data Architecture | Data Catalog | Data Documentation | Data Governance | Data Modeling | Data Monitoring | Data Quality | Dimension modeling | ELT | Embeddings | Fact-Dimension Modeling | Fact/Dimension | Generative AI | LLM | MLOps | Machine Learning | Metrics layer | Python | RAG | Retrieval-Augmented Generation | SQL | Semantic Search | Semantic layer | Snowflake | Star Schema | Test automation | Vector Databases
Education
N/A
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