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Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled data architect can be very helpful for that purpose. What is a data architect? Let’s discuss and compare them to avoid misconceptions.

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Top 10 Azure Data Engineer Job Opportunities in 2024 [Career Options]

Knowledge Hut

In-Demand Azure Data Engineer Job Roles I have explained why Microsoft data engineer jobs are on the rise and what you would benefit from them. Now, let’s see what options are available under Azure data engineer careers. Develop data models, data governance policies, and data integration strategies.

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How to become Azure Data Engineer I Edureka

Edureka

An Azure Data Engineer is a professional who is responsible for designing and implementing the management, monitoring, security, and privacy of data using the full stack of Azure data services to satisfy the business needs of an organization. Become proficient in programming languages such as Python and SQL.

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Data Engineering Learning Path: A Complete Roadmap

Knowledge Hut

Steps to Become a Data Engineer One excellent point is that you don’t need to enter the industry as a data engineer. You can start as a software engineer, business intelligence analyst, data architect, solutions architect, or machine learning engineer. What Degree is Needed to Become a Data Engineer?

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From Zero to ETL Hero-A-Z Guide to Become an ETL Developer

ProjectPro

Data Warehousing Knowledge of data cubes, dimensional modeling, and data marts is required. Data Governance Know-how of data security, compliance, and privacy. 5-Step Guide to Become an ETL Developer Get a strong education background in IT, Computer Science, or any other related field.

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14 Best Database Certifications in 2023 to Boost Your Career

Knowledge Hut

Over the past decade, the IT world transformed with a data revolution. Back when I studied Computer Science in the early 2000s, databases like MS Access and Oracle ruled. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it.