data-engineering-skills

In the author's own words, from each skill's SKILL.md.

• docker-compose

  Write, review, and modernize Docker Compose files against the current Compose Specification and the docker compose CLI. Use for authoring compose.yaml or docker-compose.yml, service dependency and healthcheck ordering, profiles, networks, volumes, secrets and configs, build contexts, migrating off V1 and the obsolete version key, or containers that fail to start, restart-loop, report unhealthy, o…

  docker-compose/SKILL.md on GitHub (opens in a new tab)

• firn

  Design, deploy, use, and troubleshoot Firn, the object-storage-backed multi-tenant vector and full-text search engine. Use for Firn REST API or embedded Python work, LanceDB-backed vector, BM25, hybrid, or multivector search, S3/GCS/MinIO storage, RAM/NVMe/object-storage caching, ingestion and index-build workflows, namespace isolation, auth, metrics, latency, or cache correctness.

  firn/SKILL.md on GitHub (opens in a new tab)

• flink

  Architect, implement, deploy, upgrade, and troubleshoot Apache Flink stream processing jobs. Use for Flink SQL, Table API, or DataStream implementation, 1.x to 2.x migration, savepoint and state compatibility, checkpoint failures, backpressure, watermark and late-data problems, Kubernetes Operator deployment, Flink CDC pipelines, or Iceberg, Paimon, and Fluss connector work.

  flink/SKILL.md on GitHub (opens in a new tab)

• fluss

  Design, deploy, and operate Apache Fluss streaming storage for sub-second real-time analytics. Use for Fluss log or primary-key table design, bucket sizing, tiering to Paimon, Iceberg, or Lance, Flink integration and Delta Join, $changelog and $binlog virtual tables, Spark access to streams, client SDK choice, or deciding between hot streaming storage and a lakehouse table.

  fluss/SKILL.md on GitHub (opens in a new tab)

• iceberg

  Design, migrate, tune, and maintain Apache Iceberg tables across query engines. Use for Iceberg schema and partition evolution, v2 to v3 upgrades, catalog selection, time travel and rollback, row-level deletes, snapshot expiry, orphan file cleanup, small-file compaction, or slow queries and metadata bloat on a lakehouse table. Covers Spark, Flink, Trino, Athena, Snowflake, REST catalogs, Polaris,…

  iceberg/SKILL.md on GitHub (opens in a new tab)

• iggy

  Deploy, configure, and build clients against Apache Iggy (Incubating), a Rust-native message streaming platform. Use for Iggy server deployment via Docker, Compose, or Kubernetes, stream, topic, and partition design, retention and consumer group setup, transport choice across QUIC, TCP, HTTP, and WebSocket, SDK usage including the Python apache-iggy package, Iggy MCP and connectors, connection fa…

  iggy/SKILL.md on GitHub (opens in a new tab)

• lance

  Design, index, query, and tune Lance datasets and LanceDB tables for ML and AI workloads. Use for vector index selection such as IVF_PQ or IVF_HNSW_FLAT, ANN recall and latency tuning, full-text and hybrid search, scalar indexes and prefiltering, dataset versioning and compaction, embedding and multimodal storage, slow vector search on object storage, or migrating ML data from Parquet. Covers bot…

  lance/SKILL.md on GitHub (opens in a new tab)

• paimon

  Design, ingest into, tune, and operate Apache Paimon tables for streaming lakehouses. Use for Paimon primary-key or append-only table design, bucket sizing, changelog producer choice, Flink CDC ingestion, compaction backlog, lookup join performance, PyPaimon, Spark reads, Iceberg compatibility, or streaming writes that produce too many small files.

  paimon/SKILL.md on GitHub (opens in a new tab)

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