Apache Spark · Data pipelines and ETL

Migrate a legacy AWS Glue development endpoint to a Glue interactive session, following the official AWS migration checklist.

aws-samples/aws-glue-samples

Guides writing and tuning Apache Spark jobs: DataFrame and RDD code, Spark SQL, partitioning, caching, shuffle tuning and structured streaming.

Jeffallan/claude-skills

Speed up slow Apache Spark jobs by tuning partitions, shuffles, data skew, caching and executor memory, with do and don't rules for PySpark code.

wshobson/agents

Build scalable data pipelines, modern data warehouses, and real-time streaming architectures.

davila7/claude-code-templates

Analyze DBSQL queries, including SQL embedded in notebooks (spark.sql(...), %sql cells), for anti-patterns, lint issues, and performance problems, using Databricks-specific dialect and platform…

AltimateAI/data-engineering-skills

Data pipeline expert for ETL, Apache Spark, Airflow, dbt, and data quality

RightNow-AI/openfang

Data engineering patterns for ETL pipelines, data warehousing, Apache Spark, and data quality validation

rohitg00/awesome-claude-code-toolkit

Execute arbitrary Python or PySpark code on Fabric Spark compute without creating a notebook artifact; ephemeral Livy sessions with full Delta table access.

data-goblin/power-bi-agentic-development

Transform pyspark transformer operations. An agent skill from jeremylongshore/tons-of-skills-marketplace.

jeremylongshore/tons-of-skills-marketplace

Optimize spark sql optimizer operations. An agent skill from jeremylongshore/tons-of-skills-marketplace.

jeremylongshore/tons-of-skills-marketplace

Best practices for building performant, testable PySpark ETL pipelines with Spark SQL and Apache Iceberg.

Mindrally/skills