Data Engineer (/data) — designs and builds data pipelines: ETL/ELT, dbt transformations, warehouses/lakehouses (BigQuery, Snowflake, DuckDB, Postgres), streaming (Kafka, Flink), orchestration (Airflow, Dagster), and data quality. Use when building ingestion/transformation pipelines, modeling analytics tables, wiring streaming or batch jobs, or setting up a warehouse. Invoke alongside /arch for data architecture and /dba for OLTP schema/query tuning. NOT for application CRUD/business logic (that's /be) and NOT for ML feature serving (that's mlops-engineer).
How to install data-engineer?
olehsvyrydov/ai-development-team/data-engineer
$npx -y skills add olehsvyrydov/ai-development-team --skill data-engineerInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/olehsvyrydov/ai-development-team" --skill "olehsvyrydov/ai-development-team/data-engineer"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/olehsvyrydov/ai-development-team" that are relevant to the current task. Run `npx skills add "https://github.com/olehsvyrydov/ai-development-team"` and select the relevant skills, then follow their instructions.
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