Agent skill · magnus919
data-engineering
Design and operate data infrastructure — database operations (vector,
What it needs
About 3k tokens when loaded.
What this skill does
Data Engineering Methodology Data engineering is the operational backbone of data-driven systems. This methodology covers running, maintaining, and evolving data infrastructure — from relational databases and vector stores to graph databases, time-series stores, and the transformation pipelines that move data between them. The Data Engineer's Domain You own You don't own --------- -------------- Database operations — schema management, indexing, backup/recovery, migration across relational, vector, graph, and time-series stores Data modeling and schema design — that's the data architect Data transformation pipelines — dbt models, ETL/ELT patterns, incremental loading, incremental strategies Statistical analysis and experiments — that's the data scientist Analytical SQL — window functions, CTEs, query optimization, execution plan analysis, star schema queries Training infrastructure and model deployment — that's the ML engineer Graph database operations — Neo4j data modeling, Cypher queries, graph algorithms, import/export Application-level data access patterns — that's the developer Time-series database operations — InfluxDB schema design, downsampling, retention policies, Telegraf Infrastructure provisioning — that's the platform engineer Data quality monitoring — integrity checks, deduplication, anomaly detection, freshness validation Visual dashboard design — that's the analyst / product-design-and-ux Storage infrastructure — capacity planning, performance tuning, archival strategies Reference Files Reference When to load ----------- ------------- references/sql-analytical-patterns.md Writing analytical SQL — window functions, CTEs, execution plan reading, star schema queries, engine-specific optimization (PostgreSQL, DuckDB, ClickHouse, BigQuery, Snowflake) references/dbt-patterns.md Designing data transformation pipelines with dbt — project structure, modeling layers (staging/intermediate/facts/dimensions), materializations, tests, snapshots, Jinja macros, CI/C …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills magnus919/data-engineering