Fenna - DataOps Engineer AI Skill

Name: Fenna - DataOps Engineer AI Skill
Brand: KissMySkills
Price: 19 USD
Availability: InStock

DataOps Engineer, Fenna AI skill by KissMySkills, cover

Senior DataOps / Pipeline Orchestration Engineer who treats orchestration as a reliability discipline, not just scheduling.

$19 this skill one payment yours forever

Claude skill package instant downloadfenna-dataops-pipeline-orchestration-engineer.skill

Library plan

Get this skill and 2,500+ others

$9/mo or $59 a year

Get Library · $9/moGet Library

Try this skill free for 7 daysTry this skill free

7-day free trial, no card
Cancel anytime
30-day money-back on your first payment

Nothing is charged. A −30% code for your first payment arrives 2 days before the trial ends.

Works inside Claude, ChatGPT, Claude Code, Codex and Cursor through one connector
Every skill, prompt pack and agent, plus AI CRM and tools during the trial
Cancel anytime

Why a subscription? How it works

Need just this skill?

One file, paid once. No updates, no connector.

Costs about the same as 2 months of Library.

$19

Pay once, keep foreverInstant download30-day money-back guarantee

As featured onProduct Hunt Fazier KittyLaunch

Works with

Secure checkout by Stripe

Trademarks of their respective owners. KissMySkills is not affiliated with or endorsed by them.

How it works

Ask Fenna something hard.

📎 fenna-dataops-pipeline-orchestration-engineer.skillLOADED ✓

Airflow, 200 DAGs: one team's backfill last Tuesday starved everyone's SLAs for 8 hours. How do I make that impossible?

CLAUDE · AS FENNA, DATAOPS ENGINEER Backfills starving production is a pools-and-priorities gap, not a people problem - give backfills a dedicated pool capped at 20-30% of worker slots so SLA capacity is untouchable, set priority_weight so scheduled runs preempt catch-up runs, and default max_active_runs=1 on heavy DAGs. Then the process piece: any backfill over a size threshold gets announced with a window - for visibility, not permission. Also verify the scheduler wasn't the real victim: 8 hours of starvation across 200 DAGs often includes parsing contention. Celery or Kubernetes executor? The slot math differs.

Or have every skill inside your AI.

0:16 · no sound

Get all 2,500+ with Library · $9/mo →

Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com

// the file itself

Read it before you buy it.

The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.

// the skill your AI runs on

You are Fenna, a Senior DataOps and Pipeline Orchestration Engineer who maps cross-DAG dependencies, verifies idempotency before a backfill, and anchors SLAs to data freshness. You have been activated to keep Airflow and Dagster pipelines trustworthy.

Drop Fenna into Claude and get a Senior DataOps / Pipeline Orchestration Engineer who has run Airflow and Dagster in production for orchestration estates with hundreds of DAGs, the kind where a quietly re-triggered backfill or a missed SLA doesn't show up as an error, it shows up three days later as a stakeholder asking why the executive report was wrong. Fenna does not treat orchestration as "just scheduling." She treats it as a discipline with its own failure modes: dependency graphs that look correct until a retry fires out of order, backfills that silently double-process a partition because idempotency was assumed rather than verified, and SLA monitoring that watches task duration but not the thing the business actually cares about, namely when the data lands and whether it's trusted. Fenna covers the full pipeline orchestration surface: DAG design and dependency management, backfill strategy, SLA definition and breach alerting, pipeline testing (data contract tests, freshness checks),

SKILL.md · 182 lines · instant download

// what's inside

What's inside this skill

Orchestration redesign with dependency and retry policy
An alerting and SLA plan defined per DAG
Idempotent backfill pattern that will not clobber data
Data quality gate checklist for every pipeline

Data engineers and analytics teams whose Airflow jobs fail silently overnight

// two ways to get it

Use it inside your AI, or download it once.

Library plan

This skill and 2,500+ others, inside your chat

$9/mo cancel anytime, or $59 a year

All 2,500+ skills, prompt packs and agents, loaded the moment you ask
Nothing to download or paste: connect once in Claude, ChatGPT, Claude Code or Cursor
New skills every week and 10 catalog files a month to download

Get Library · $9/mo Try it free for 7 days

Compare Library, AI CRM and Both

Buy once

Just this skill, as a file

$19 one payment

Download after checkout and paste it into any AI chat
One file, no updates, no connector
30-day money-back guarantee

Already on Library or Both? This one is included, no need to buy the file.

Works with

Trademarks of their respective owners. KissMySkills is not affiliated with or endorsed by them.

// ask your assistant

Or let your AI set up this skill for you.

Go to kissmyskills.com/pages/connector and set up the "Fenna - DataOps Engineer AI Skill" skill (handle: fenna-dataops-pipeline-orchestration-engineer) for me

Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →

What you're actually buying

Senior DataOps / Pipeline Orchestration Engineer who treats orchestration as a reliability discipline, not just scheduling.

Fenna covers the full pipeline orchestration surface: Airflow and Dagster DAG design, cross-DAG and cross-team dependency management, backfill strategy, SLA definition and breach alerting, pipeline testing (data contract tests, freshness checks), orchestrator scaling (worker pools, executor choice), and pipeline observability and lineage.

Who it's for

Data platform teams and orchestration owners who need DAG dependency maps, backfill runbooks, and SLA definitions anchored to real data freshness, not task-duration dashboards that look fine while the business-facing table is stale.

Key capabilities

Explicit cross-DAG and cross-team dependency mapping, including implicit dependencies nobody documented
Backfill runbooks that verify idempotency before approving any rerun or reprocessing plan
Freshness-based SLA specifications anchored to when data is actually consumed, not task runtime
Data contract and freshness tests wired into the DAG so a bad-data run fails visibly
Executor and worker pool scaling plans mapped to real DAG/task volume and scheduler parsing time

How to use it

Paste Fenna's SKILL.md into your Claude Project Instructions (or any AI system prompt), then describe your DataOps & Pipeline Orchestration Engineer problem. Works with Claude, ChatGPT, and any AI chat. Under 2 minutes to install.

// how to install Under 2 minutes

Four steps. Any AI chat.

01
Download the file
After checkout, the download link lands in your inbox. Save the .skill file: Claude takes it as it is.
02
Open your AI chat
Any AI chat you already use: Claude, ChatGPT, Gemini, Grok, Copilot or another.
03
Add it to your AI
Claude: Settings → Capabilities → Skills, upload the .skill file. ChatGPT, Gemini and others: open the .skill file like a .zip archive and paste SKILL.md into custom instructions or Project instructions.
04
Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.

No technical knowledge required.

With Library there is nothing to download. Connect your AI once, then just ask: "Load Fenna from KissMySkills."

Setup guide → Library · $9/mo →

// faq

Questions about this product

What AI tools does this work with?+

Claude, ChatGPT, or any AI chat that accepts a system prompt or project instructions. Claude Projects gives the best results.

How do I install it?+

Paste the SKILL.md content into your Claude Project Instructions or your AI's system prompt. Under 2 minutes, no setup required.

Is this a course or a tool?+

It's a skill file, not a course. One file that turns your AI into a configured DataOps & Pipeline Orchestration Engineer ready to work on your DataOps & Pipeline Orchestration Engineer problem immediately.

A backfill double-processed a partition, what does Fenna check before it happens again?+

Fenna never approves a backfill on an unverified "should be fine." She confirms idempotency for the affected partitions explicitly first, since re-running a non-idempotent task is exactly how a backfill and a scheduled run end up double-writing the same partition.