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Found 133 Skills
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
Guide users through the Amore CLI for macOS app distribution — setup, releasing, code signing, notarization, DMG creation, S3 hosting, Sparkle updates, licensing, and configuration. Use this skill whenever the user mentions Amore, amore CLI, macOS app distribution outside the App Store, Sparkle updater setup, appcast.xml, notarization workflows, DMG creation, or self-publishing macOS apps. Also use when the user asks about release automation, S3 bucket hosting for app updates, EdDSA signing keys, or licensing with Stripe for macOS apps.
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
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 when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.
Data pipeline expert for ETL, Apache Spark, Airflow, dbt, and data quality
Generate a paid social creative brief from a whitelisted or Spark Ad creator post, covering hook analysis, messaging angle, audience targeting, caption variants, and placement recommendations. This skill should be used when turning a creator post into a paid ad brief, writing a creative brief for whitelisted content, briefing the paid team on creator content, generating Spark Ads briefs from organic posts, creating paid media briefs from influencer content, translating UGC into a paid social strategy, building a media buyer brief from a creator video, preparing whitelisted content for ad spend, or generating placement recommendations for boosted creator content. For adapting captions into ad copy variants, see paid-ad-copy-adapter. For organic repost captions, see organic-repost-caption-writer. For FTC compliance, see ftc-disclosure-spot-checker.
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.
Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.
Master enterprise-grade Scala development with functional programming, distributed systems, and big data processing. Expert in Apache Pekko, Akka, Spark, ZIO/Cats Effect, and reactive architectures. Use PROACTIVELY for Scala system design, performance optimization, or enterprise integration.
V8 JIT Compilation, TurboFan, Maglev, Sparkplug. Load this when needing to understand V8's compilation pipeline, JIT optimization, or JITless mode.
Implement end-to-end Medallion Architecture (Bronze/Silver/Gold) lakehouse patterns in Microsoft Fabric using PySpark, Delta Lake, and Fabric Pipelines. Use when the user wants to: (1) design a Bronze/Silver/Gold data lakehouse, (2) set up multi-layer workspace with lakehouses for each tier, (3) build ingestion-to-analytics pipelines with data quality enforcement, (4) optimize Spark configurations per medallion layer, (5) orchestrate Bronze-to-Silver-to-Gold flows via notebooks. Triggers: "medallion architecture", "bronze silver gold", "lakehouse layers", "e2e data pipeline", "end-to-end lakehouse", "data lakehouse pattern", "multi-layer lakehouse", "build medallion", "setup medallion".
Data engineering patterns for ETL pipelines, data warehousing, Apache Spark, and data quality validation