Data Quality Engineer

12 096 890 Ft (HUF)/yr

5 815,81 Ft (HUF)/hr

500 811 Ft (HUF)/yr

The average data quality engineer gross salary in Hungary is 12 096 890 Ft or an equivalent hourly rate of 5 816 Ft. In addition, they earn an average bonus of 500 811 Ft. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Hungary. An entry level data quality engineer (1-3 years of experience) earns an average salary of 8 687 858 Ft. On the other end, a senior level data quality engineer (8+ years of experience) earns an average salary of 13 766 677 Ft.

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Salary Potential

16 594 028 Ft (HUF)

37 %

Based on our compensation data, the estimated salary potential for Data Quality Engineer will increase 37 % over 5 years.

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Country Overview

Hungary

Cost of living is calculated based on accumulating the cost of food, transportation, health services, rent, utilities, taxes, and miscellaneous.

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Hungary is a landlocked country in Central Europe. Spanning much of the Carpathian Basin, it is bordered by Slovakia to the north, Ukraine to the northeast, Romania to the east and southeast, Serbia to the south, Croatia and Slovenia to the southwest, and Austria to the west. Hungary lies within the drainage basin of the Danube River and is dominated by great lowland plains. It has a population of 9.6 million, consisting mostly of ethnic Hungarians (Magyars) and a significant Romani minority. Hu

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Disclaimer
This page is an excerpt of the much more complete compensation information available in ERI's Assessor Series.

ERI's compensation data are based on salary surveys conducted and researched by ERI. Cost of labor data in the Assessor Series are based on actual housing sales data from commercially available sources, plus rental rates, gasoline prices, consumables, medical care premium costs, property taxes, effective income tax rates, etc.

Job Description
Assures critical data is accurate, complete, timely, and reliable across pipelines and analytics. Designs and automates data quality controls, validates transformations, monitors data products in production, and partners with Data Engineering, Analytics, and Business stakeholders to prevent defects, resolve incidents, and improve trust in metrics and models. Defines data quality requirements and test strategies for priority datasets, reports, and models.
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