Skills for your AI
Guides database administrators through data warehouse design, ETL optimization, integration, performance tuning, security, governance, maintenance, and analytics. Use when the user asks about data warehousing fundamentals, schema or architecture choices, ETL w
Plans and documents HRIS data migrations and integrations, covering mapping, cleansing, transformation, migration planning, third-party integration, ETL workflows, security review, change management, testing, decommissioning, and post-migration monitoring. Use
Structures PyTorch code into LightningModules, configures Trainers, LightningDataModules, callbacks, logging, and distributed strategies. Use when converting PyTorch models to Lightning, setting up multi-GPU/TPU training, building data pipelines, adding checkp
Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use w
Designs and maintains scalable data pipelines, ETL/ELT jobs, data models, orchestration, and data quality checks. Use when the user needs pipeline architecture, ETL/ELT scripts, data quality validation, performance optimization, data modeling, orchestration, s
Designs ML deployment pipelines, RAG/LLM integrations, monitoring, data pipelines, inference optimization, security compliance, and MLOps advisory plans. Use when a user needs to productionize a model, build RAG, set up drift monitoring, design data pipelines,
Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks, Snowpipe), Cortex AI functions, Cortex Agents, Snowpark Python, dbt integration, performance tuning, and security hardening.
