1. What is the average salary of a Data Architect V?
The average annual salary of Data Architect V is $177,210.
In case you are finding an easy salary calculator,
the average hourly pay of Data Architect V is $85;
the average weekly pay of Data Architect V is $3,408;
the average monthly pay of Data Architect V is $14,767.
2. Where can a Data Architect V earn the most?
A Data Architect V's earning potential can vary widely depending on several factors, including location, industry, experience, education, and the specific employer.
According to the latest salary data by Salary.com, a Data Architect V earns the most in San Jose, CA, where the annual salary of a Data Architect V is $222,398.
3. What is the highest pay for Data Architect V?
The highest pay for Data Architect V is $210,762.
4. What is the lowest pay for Data Architect V?
The lowest pay for Data Architect V is $146,645.
5. What are the responsibilities of Data Architect V?
Data Architect V designs and builds databases for data storage or processing. Develops strategies for warehouse implementation, data acquisition and access, and data archiving and recovery. Being a Data Architect V builds data models and defines the structure, attributes and nomenclature of data elements. May evaluate new data sources for adherence to the organization's quality standards and ease of integration. Additionally, Data Architect V requires a bachelor's degree. Typically reports to a supervisor or manager. The Data Architect V works autonomously. Goals are generally communicated in "solution" or project goal terms. May provide a leadership role for the work group through knowledge in the area of specialization. Works on advanced, complex technical projects or business issues requiring state of the art technical or industry knowledge. To be a Data Architect V typically requires 10+ years of related experience.
6. What are the skills of Data Architect V
Specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.
1.)
Analysis: Analysis is the process of considering something carefully or using statistical methods in order to understand it or explain it.
2.)
Data Modeling: Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques.
3.)
Data Quality: Data quality refers to the condition of a set of values of qualitative or quantitative variables. There are many definitions of data quality but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning". Alternatively, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as data volume increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose. People's views on data quality can often be in disagreement, even when discussing the same set of data used for the same purpose. Data cleansing may be required in order to ensure data quality.