Snowflake
1
Snowflake Data Engineering
Strategy & Architecture
• Snowflake platform roadmap
• Lakehouse & data mesh reference architecture
• Cost, performance, and credit optimization
• Tool rationalization (dbt, Snowpark, Spark, Airflow, etc.)
Data Modeling & Engineering
• Business-driven dimensional & vault models
• ELT, CDC, and streaming pipelines
• Data quality, observability, lineage
Platform & Operations
• Security, governance, HA / DR
• Query tuning & warehouse optimization
• Cross-region, cross-cloud sharing
2
Snowflake Intelligence
Analytics, ML, and AI where the data lives
We design and operationalize Snowflake Intelligence solutions that bring analytics and ML directly into Snowflake, secure on top of 1st-party structured, unstructured, or semi-structured data.
Capabilities include:
• Snowpark ML & feature engineering
• Time-series forecasting & anomaly detection
• In-database analytics & model execution
• Already data products & ML observability metrics
• Integration with BI and ML platforms
RESULT: Faster insights with governed, scalable analytics—without data movement.
3
Snowflake Apps
• App architecture, packaging, and deployment
• Secure data sharing & marketplace enablement
• Multi-tenant design & versioning
• Governance, billing, and operations
Streamlit on Snowflake
• Interactive data apps & dashboards
• Embedded analytics for business users
• Rapid prototype → production
• Role-based access & security integration
RESULT: Secure, scalable apps delivered directly inside Snowflake.