Engineer Data Quality

kr 776 361 (NOK)/yr

kr 373,25 (NOK)/hr

kr 32 141 (NOK)/yr

The average engineer data quality gross salary in Norway is kr 776 361 or an equivalent hourly rate of kr 373. In addition, they earn an average bonus of kr 32 141. Salary estimates based on salary survey data collected directly from employers and anonymous employees in Norway. An entry level engineer data quality (1-3 years of experience) earns an average salary of kr 556 815. On the other end, a senior level engineer data quality (8+ years of experience) earns an average salary of kr 877 805.

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Salary Potential

kr 890 088 (NOK)

15 %

Based on our compensation data, the estimated salary potential for Engineer Data Quality will increase 15 % over 5 years.

Education

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Country Overview

Norway

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

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Norway, officially the Kingdom of Norway, is a Nordic country comprising the western and northernmost parts of the Scandinavian Peninsula in Northern Europe, the remote Arctic island Jan Mayen and the archipelago Svalbard. Bouvet Island, located in the Subantarctic, is a dependency, and not a part of the Kingdom; Norway also claims the Antarctic territories of Peter I Island and Queen Maud Land. Norway has a population of approximately 5.6 million, and a total area of 385,207 square kilometres (

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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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