Data Analytics Engineer (remote)

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Profession Services
Munkavégzés helye

Távmunka / Remote

Egyéb juttatások
- Cafeteria
- Szakmai tréningek
- Sport támogatás
Munkaidő, foglalkoztatás jellege
- Teljes munkaidő
- Alkalmazotti jogviszony
- Rugalmas munkaidő
Elvárt technológiák
- ANALYTICS BI TESTING SQL GIT SAP ORACLE ERP PYTHON DEVOPS POWER BI AGILE
Biztosított eszközök
- Laptop
- Workstation
Elvárások
- Angol felsőfok
- 3-5 év tapasztalat
- Felsőoktatási szakképzés

Állás elmentve

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A hirdetés adatait sikeresen elküldte az email címére.

Céginformáció

This role is for someone who enjoys the craft of data modeling - using Microsoft Fabric, dbt, and Power BI to make data clean, testable, and usable.

Feladatok

Design and scale analytics-ready data models using dbt in Microsoft Fabric
Transform raw enterprise data into trusted, business-ready datasets
Build and own Power BI semantic models and DAX logic (this is a hard requirement)
Ensure data quality, testing, documentation, and governance end-to-end
Optimize performance across large-scale datasets
Collaborate with global stakeholders (US-based leadership)
Help define best practices and standards in a still-evolving data organization

Elvárások

3+ years of experience in analytics engineering / data engineering
Fluent English (interviews and daily work are fully in English)
Strong SQL skills, hands-on dbt data modeling experience
Practical Microsoft Fabric experience (Power BI, Lakehouse, Warehouse, OneLake)
Advanced Power BI + DAX knowledge (developer level, not just reporting)
Git-based version control, CI/CD mindset

Juttatások

Fully remote role (no office attendance required)
Motivating compensation, aligned with seniority and impact
Cafeteria
Long-term, globally relevant projects on a modern data platform
US collaboration without night shifts
Modern tooling
Strong company culture with frequent events, sports support, subsidized meals

Előnyt jelent

Experience with SAP (ECC / S4HANA), Oracle EBS, or enterprise ERP data models
Exposure to Salesforce, Finance, HR, or manufacturing data domains
Python or scripting languages
Data governance, lineage, observability tooling
Agile / DevOps environments