Description review

PySpark Data Engineer

Joyful Craftsmen AG · Czechia, Switzerland · back to the listing

HR standards

56/100

needs work

Title ↔ description

89/100

strong

Reads as

Data Engineer

100% confident

How others title the same work

Large employers

  • Data Engineer, Product Analytics Meta
  • Senior Staff Data Engineer Mozilla
  • Staff, Analytics Engineer, GTM Data Science & Analytics Twilio
  • Senior Software Engineer - Data Platform Coinbase
  • Senior Security Data Engineer Doordash

Startups

  • Business Intelligence Engineer GoSats
  • IPinfo.io | Data Engineer | REMOTE (Anywhere) | Full-time IPinfo.io
  • Senior Data Engineer Camber
  • Senior Data Engineer Instrumentl
  • Cardog | Toronto, Canada or REMOTE | Full-time Cardog

What the listing never says

  • 21 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

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.

We are the Microsoft Data Platform Competence Center – leading experts in Microsoft data technologies. Our team has hands-on experience with the full spectrum of modern data solutions including Azure Data Factory, Synapse Analytics, Microsoft Fabric, Power BI, Purview, Azure SQL Database, Databricks, Palantir, and more.
We constantly learn, experiment, and refine our engineering practices, implementing new innovations across the data ecosystem.

Our team has grown to 40 specialists operating in both the Czech Republic and Switzerland.

What you will do as a PySpark Data Engineer

• Design, build and optimize scalable data pipelines using Python & PySpark

• Work with modern data platforms (Palantir Foundry / Databricks / similar)

• Integrate data from finance and insurance source systems

• Support data delivery for analytics and reporting solutions (e.g. Power BI)

• Ensure data quality, reliability and performance of pipelines

• Collaborate with Business, Analytics and Engineering teams

• Support deployment, monitoring and production operations

What we expect

• Strong experience in Python & PySpark

• Experience with Spark-based data platforms (Palantir Foundry is a big plus)

• Solid experience in data engineering and building ETL/ELT pipelines

• Strong knowledge of SQL and large-scale data processing

• Experience from financial services (insurance is preferred)

• Experience with Git and CI/CD pipelines

• Good communication skills in English

What we offer you

• Budget for personal development (courses, conferences, certifications)

• Opportunity to work remotely on international projects

• Work from the comfort of your home or from our new design office

• We value our time – no overtime

• Access to our company library for inspiration

• Attractive mobile plan, Multisport card, and fuel card

• Barbecues on the terrace and plenty of other team events

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: 12 points (from 68 before penalties). Reviewed 21 Sep 2026.