Data Engineering (7 configs)

AI agent configuration files from top Data Engineering repositories on GitHub.

★ 45k
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
CLAUDE.md+AGENTS.md 100 lines workfloworchestrationetlpython
★ 43k
Apache Spark - A unified analytics engine for large-scale data processing
CLAUDE.md+AGENTS.md 110 lines big-dataanalyticsdistributed-computingscala
★ 40k
AGENTS.md for Apache Spark — unified analytics engine. Covers RDD, DataFrame API, and distributed execution patterns.
AGENTS.md 110 lines analyticsdistributedscalabig-data
★ 38k
AGENTS.md for Apache Airflow — workflow orchestration. Covers DAG definition, operators, and scheduler architecture.
AGENTS.md 95 lines workfloworchestrationpythondag
★ 28k
AGENTS.md for Apache Kafka — distributed event streaming platform. Covers broker architecture, partitioning, and Java patterns.
CLAUDE.md for dbt — data build tool for analytics. Covers model dependencies, Jinja macros, and adapter patterns.
CLAUDE.md 65 lines dbtanalyticssqlpython
AGENTS.md for Datacoves — dbt + DuckDB analytics platform. Covers data pipeline patterns, YAML conventions, and SQL standards.
AGENTS.md 65 lines dbtduckdbanalyticssql