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senior-data-engineer

senior-data-engineer is a skill for Claude Code from yezannnnn/agentGroup. It costs 85 tokens per session (6,001 once invoked), scanned A, original, MIT.

A guide for building data systems that collect, transform, validate, store, and move information. ETL and ELT are common ways to load data and transform it for use; tools covered include Python, SQL, Spark, Airflow, dbt, and Kafka.

In plain words
What is it for?
Use it to design batch or streaming pipelines, build ETL or ELT processes, model data, handle late-arriving records, add validation, monitor freshness, and tune Spark or Airflow jobs.
Why use it?
It helps turn vague data-system requirements into choices about pipelines, data models, quality checks, scheduling, and real-time processing. It also provides guidance for diagnosing slow or unreliable data jobs.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the engineering-skills plugin — 17 skills shipped together

not rated 149repo 3mo ago A scan 85 tokens original MIT

Good fit Use it to design batch or streaming pipelines, build ETL or ELT processes, model data, handle late-arriving records, add validation, monitor freshness, and tune Spark or Airflow jobs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yezannnnn/agentgroup/senior-data-engineer
View source ↗ yezannnnn/agentGroup
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yezannnnn/agentGroup --skill senior-data-engineer
Clone the repo
git clone --depth 1 https://github.com/yezannnnn/agentGroup

Made for: Claude Code.

Or install engineering-skills, the plugin that ships this one along with the rest of its 17 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for senior-data-engineer

README.md
[![agentmods](https://agentmods.dev/badge/skills/yezannnnn/agentgroup/senior-data-engineer.svg)](https://agentmods.dev/skills/yezannnnn/agentgroup/senior-data-engineer)
Your own site
<a href="https://agentmods.dev/skills/yezannnnn/agentgroup/senior-data-engineer"><img src="https://agentmods.dev/badge/skills/yezannnnn/agentgroup/senior-data-engineer.svg" alt="Measured on agentmods" height="20"></a>
Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,001 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00085 $0.06001
Opus 5 $0.00043 $0.03001
Sonnet 5 $0.00017 $0.01200
Haiku 4.5 $0.00009 $0.00600

Measured 8d ago against content hash 15dca8b0e5db, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

senior-data-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/data_quality_validator.py, scripts/etl_performance_optimizer.py, scripts/pipeline_orchestrator.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

jarvis/skills/engineering-team/senior-data-engineer/SKILL.md · 993 lines

How it starts

The opening of the file, as written. The whole thing — 993 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Senior Data Engineer

Production-grade data engineering skill for building scalable, reliable data systems.

Table of Contents

  1. Trigger Phrases
  2. Quick Start
  3. Workflows
  4. Architecture Decision Framework
  5. Tech Stack
  6. Reference Documentation
  7. Troubleshooting

Trigger Phrases

Activate this skill when you see:

Pipeline Design:

  • "Design a data pipeline for..."
  • "Build an ETL/ELT process..."
  • "How should I ingest data from..."
  • "Set up data extraction from..."

Architecture:

  • "Should I use batch or streaming?"
  • "Lambda vs Kappa architecture"
  • "How to handle late-arriving data"
  • "Design a data lakehouse"

Data Modeling:

  • "Create a dimensional model..."
  • "Star schema vs snowflake"
  • "Implement slowly changing dimensions"
  • "Design a data vault"

Data Quality:

  • "Add data validation to..."
  • "Set up data quality checks"
  • "Monitor data freshness"
  • "Implement data contracts"

Performance:

  • "Optimize this Spark job"
  • "Query is running slow"
  • "Reduce pipeline execution time"
  • "Tune Airflow DAG"

Quick Start

Core Tools

# Generate pipeline orchestration config
python scripts/pipeline_orchestrator.py generate \
  --type airflow \
  --source postgres \
  --destination snowflake \
  --schedule "0 5 * * *"

# Validate data quality
python scripts/data_quality_validator.py validate \
  --input data/sales.parquet \
  --schema schemas/sales.json \
  --checks freshness,completeness,uniqueness

# Optimize ETL performance
python scripts/etl_performance_optimizer.py analyze \
  --query queries/daily_aggregation.sql \
  --engine spark \
  --recommend

Read the full file on GitHub · 993 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 993 lines · 85 tokens per session scan A 15dca8b0e5db

Subscribe to this mod's changes

senior-data-engineer is a skill published in the GitHub repository yezannnnn/agentGroup (149 stars, last pushed 3mo ago), licensed MIT. It adds 85 tokens to every session and 6,001 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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