Data Engineering

Build React components with TypeScript, Tailwind CSS, and React Query for the Medellin Spark platform. Use when implementing UI features, creating components, managing state, or optimizing frontend performance. Specializes in React hooks, shadcn/ui components, and Supabase integration.

Calculate computed columns (Weighted Forecast, Net Amount, Net Weighted Amount) for deal/opportunity data. Use for financial calculations in the pipeline.

Guide for implementing DefectDojo - an open-source DevSecOps, ASPM, and vulnerability management platform. Use when querying vulnerabilities, managing findings, configuring CI/CD pipeline imports, or working with security scan data. Includes MCP tools for direct API interaction.

PostCSS configuration template and validation logic for Tailwind CSS processing with Autoprefixer. Includes 4 required standards (required base plugins, critical plugin order with tailwindcss first and autoprefixer last, file naming as postcss.config.js, required dependencies). Use when creating or auditing postcss.config.js files to ensure correct CSS build pipeline.

Master cloud platforms and DevOps tools including Docker, Kubernetes, Terraform, AWS, and CI/CD pipelines. Use when building infrastructure, containerizing applications, or setting up deployment automation.

MongoDB Atlas cloud database management including clusters, schemas, aggregation pipelines, and Prisma ORM integration. Activate for MongoDB queries, schema design, indexing, and Atlas administration.

Execute SQL queries against Snowflake data warehouse using Python connector. Supports password, key-pair, and SSO/OAuth authentication. Use for ad-hoc queries, data extraction, and schema exploration. Output in JSON, table, or CSV format.

Creates CI/CD pipeline configurations for automated testing and deployment

CI/CD pipeline failure resolution with autonomous iteration loops. Local validation → branch & PR creation → CI monitoring → iteration until green. Proven patterns for GitHub Actions, includes role-specific adaptations. Use when CI pipeline failures occur, GitHub Actions errors detected, autonomous error resolution needed, PR creation for fixes required. Triggers on ci pipeline failures, github actions errors, autonomous ci resolution, ci iteration, pr creation for errors, pipeline validation, test failures in ci, build failures in ci, continuous integration debugging.

Generate comprehensive test suites for Scrapy spiders, pipelines, and middlewares when implementing tests or improving coverage. Creates unit tests, integration tests, and contract tests with proper fixtures and mocking.

Analyze a project and implement CI/CD pipelines tailored to its tech stack and deployment target. This skill should be used when a project is ready for automated testing and/or deployment. Generates GitHub Actions workflows, deployment scripts, and secrets documentation. Works as a standalone utility on any project.

Integrate Databricks Genie rooms as tools in agent workflows. Use when integrating Genie spaces with AI agents, querying Genie rooms programmatically via SDK or MCP, managing Genie conversations and polling, handling Genie API responses and errors, or building tool-calling agents that use Genie as a data source. Covers SDK patterns, MCP tool integration, conversation management, error handling, and performance optimization for Genie-based agent tools.

Modern deployment with Databricks Asset Bundles (DAB), supporting multi-environment configurations and CI/CD integration.

ALWAYS USE when working with Dagster assets, resources, IO managers, schedules, sensors, or dbt integration.CRITICAL for: @asset decorators, @dbt_assets, DbtCliResource, ConfigurableResource, IO managers, partitions.Enforces CATALOG-AS-CONTROL-PLANE architecture - ALL Iceberg writes via catalog (Polaris/Glue).Provides pluggable orchestration patterns abstractable to Airflow/Prefect.Compute abstraction: DuckDB (default), Spark, Snowflake - all via dbt.

CI/CD pipelines, containerization, Kubernetes, and infrastructure as code patterns

Manage SQL Server database connections with ADODB, connection pooling, and retry logic. Use this skill for robust database connectivity in the extraction pipeline.

Translation Manager for this repo: Supabase-backed translations, admin UI under /admin/translation-manager with Home live preview and click-to-select translation, Edge Functions (translations-get/admin/suggest), build-time translation pipeline, and security hardening. Use when planning or editing translation manager UI, Supabase schema/migrations, translation scripts (seed/pull), Edge Functions, translation auth, or troubleshooting translation data/AI suggestions.

Production deployment and operationalization of AI agents on Databricks. Use when deploying agents to Model Serving, setting up MLflow logging and tracing for agents, implementing Agent Evaluation frameworks, monitoring agent performance in production, managing agent versions and rollbacks, optimizing agent costs and latency, or establishing CI/CD pipelines for agents. Covers MLflow integration patterns, evaluation best practices, Model Serving configuration, and production monitoring strategies.

Guide for using Docker - a containerization platform for building, running, and deploying applications in isolated containers. Use when containerizing applications, creating Dockerfiles, working with Docker Compose, managing images/containers, configuring networking and storage, optimizing builds, deploying to production, or implementing CI/CD pipelines with Docker.

Expert in event-driven architecture using Kafka. Use this for designing topics, schemas, and processing logic for asynchronous tasks.