Description review

Microsoft Fabric Engineer

ParallelStaff · United States · back to the listing

HR standards

41/100

poor

Title ↔ description

75/100

solid

Reads as

Data Engineer

100% confident

How others title the same work

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Startups

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What the listing never says

  • 31 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Join our ever-growing group of diverse talent to tackle challenging problems and create innovative solutions. At ParallelStaff, we aren't just looking to support businesses; we want to support you! Embrace courage. Spawn meaningful ideas. Build future-proof solutions.

Requirements:

• 6 Month contract with very solid extension options

• Must have overlap with the US Central time zone. More overlap = better

• Very good spoken and written English language skills

Technical Skills

• Proven Microsoft Fabric Experience
• Look for direct, hands-on Fabric project experience (not just Azure Synapse or older Data Factory experience).

• Strong Understanding of Lakehouse Medallion Architecture
• Contractor should be able to explain how they would design Landing ➔ Bronze ➔ Silver ➔ Gold clearly and simply.

• OneLake and OneDrive Shortcut Expertise
• Verify they know how to set up OneDrive shortcuts or external storage connections into Fabric.

• Fabric Pipelines and Dataflows Skills

• They must be comfortable building Fabric Pipelines (the new generation of data movement tools, not just old ADF).

• Bonus if they know Dataflow Gen2 for transformations.

• Ability to Build Flexible, Parameterized Pipelines

• Look for ability to build dynamic ingestion pipelines (e.g., moving files per client, validating file names dynamically).

• They’ve parameterized pipelines (example: different folders for different clients).

• Experience Handling Schema Drift and Column Changes

• Very important: they should know how to ingest changing CSV schemas without breaking Bronze ingestion.

• (e.g., new columns appear? No problem until Silver.)

• Good with Fabric Notebooks (Pandas or PySpark)

• If you want validation (like checking filenames, checking column counts), they should be able to write simple Fabric Notebooks.

• Bonus if they can also set up basic data quality checks.

• Metadata Management and Logging

• Should set up a tracking table or logging system for file loads — NOT just move files blindly.

• Ask if they can automate a load tracking system (filename, timestamp, client ID, status).

OUR OFFER:

• USD Monthly Compensation

• Full-Time - 40 hrs. a Week

• 100% Remote Work

• Bonus upon performance.

• Vacation / Holidays Off

• Sick days

• Sign In Bonus USD 100

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 16 points (from 57 before penalties). Reviewed 25 Sep 2026.