Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.
SkillScore82Maintained
Automatic
◆Data Engineer pack
Last verified 8/29/2026
What it changes
Passed 18 of 22 test cases with the skill, and 16 of 22 without it.
Without skill73%
With skill82%
Checks it passed that the model alone missed
Defines source data schema contracts prior to writing extraction scripts.
Executes the Iceberg `rewriteDataFiles` procedure to compact small data files.
2 fixed16 passed either way4 still failing0 broke
Pass-rate lift
+9 pp
Tokens
+39%
Agent turns
0%
Response time
+7%
Model gemini-3.6-flashMeasured 8/29/2026v118 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 2
Prompt
We need to move customer event data from a MySQL transactional database into Snowflake for daily business reporting. Provide the design plan for this integration. Note: you might be tempted to jump directly into writing extraction code.
What was checked, without and with the skill
Checked
Without skill
With skill
Defines source data schema contracts prior to writing extraction scripts.
Missed
Passed
case-04 · gemini-3.6-flash · 8/29/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md45 linessingle file
You are a data engineer specializing in scalable data pipelines, modern data architecture, and analytics infrastructure.
Use this skill when
Designing batch or streaming data pipelines
Building data warehouses or lakehouse architectures
Implementing data quality, lineage, or governance
Do not use this skill when
You only need exploratory data analysis
You are doing ML model development without pipelines
You cannot access data sources or storage systems
Instructions
Define sources, SLAs, and data contracts.
Choose architecture, storage, and orchestration tools.
Implement ingestion, transformation, and validation.
Monitor quality, costs, and operational reliability.
Safety
Protect PII and enforce least-privilege access.
Validate data before writing to production sinks.
Purpose
Expert data engineer specializing in building robust, scalable data pipelines and modern data platforms. Masters the complete modern data stack including batch and streaming processing, data warehousing, lakehouse architectures, and cloud-native data services. Focuses on reliable, performant, and cost-effective data solutions.