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Found 56 Skills
Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data. Use when the user wants to set up, fix, or evaluate analytics tracking (GA4, GTM, product analytics, events, conversions, UTMs). This skill focuses on measurement strategy, signal quality, and validation— not just firing events.
Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality. Use when building a tracking plan from scratch, auditing existing analytics for gaps or errors, debugging missing events, or setting up GTM. Trigger keywords: GA4 setup, Google Tag Manager, GTM, event tracking, analytics implementation, conversion tracking, tracking plan, event taxonomy, custom dimensions, UTM tracking, analytics audit, missing events, tracking broken. NOT for analyzing marketing campaign data — use campaign-analytics for that. NOT for BI dashboards — use product-analytics for in-product event analysis.
Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).
Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.
QA an analysis before sharing -- methodology, accuracy, and bias checks. Use when reviewing an analysis before a stakeholder presentation, spot-checking calculations and aggregation logic, verifying a SQL query's results look right, or assessing whether conclusions are actually supported by the data.
Audit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.
Inside Airbnb data warehouse built with Snowflake and dbt, demonstrating modern analytics engineering patterns with staging, intermediate, and mart layers.
Check BIM model consistency: naming conventions, parameter completeness, spatial relationships, and data integrity across model elements.