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Found 65 Skills
Data engineering patterns for ETL pipelines, data warehousing, Apache Spark, and data quality validation
Generates the Data Engineering team weekly/sprint status report from Azure DevOps. Organized by Epic, with objectives, on/off track status, risks, completed and planned items per area, clickable ADO links, and unplanned items flagged. Use when the user asks for a Data Engineering sprint report, weekly report, current sprint status, activities report, or sprint summary.
End-to-end data engineering pipeline using MinIO, Airbyte, PostgreSQL, DBT, and Airflow with medallion architecture (Bronze/Silver/Gold layers)
Claude Code skills for analytics and data engineers working with dbt, Snowflake, and data pipelines
Comprehensive study guide covering data engineering concepts, tools, and best practices for learning and reference
Infrastructure-as-Code patterns for data engineering using Terraform to provision AWS resources (S3, EC2, IAM)
End-to-end ETL pipeline for Harvard Art Museums API with SQL analytics and Streamlit visualization
End-to-end data engineering and analytics application using Harvard Art Museums API with ETL pipelines, SQL analytics, and Streamlit visualization
Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations. Covers feature stores (Feast, Tecton), embedding pipelines, chunking strategies, orchestration (Dagster, Prefect, Airflow), dbt transformations, data versioning (LakeFS), and experiment tracking (MLflow, W&B).
You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.
Delta Lake integration with cloud storage (S3, GCS, Azure). Covers storage_options, PyArrow filesystem, time travel, and partitioned writes.
Using DuckDB with remote cloud storage via HTTPFS extension, fsspec, and Delta Lake integration. Covers S3, GCS, Azure, and S3-compatible endpoints.