Data Architect Programming Language Software Engineering 
AltexSoft
FEBRUARY 11, 2023
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.
Knowledge Hut
MAY 3, 2023
Although the titles of these jobs are frequently used interchangeably, they are separate and call for different skill sets, which results in the difference of the salaries for data engineers and data analysts. A data analyst is responsible for analyzing large data sets and extracting insights from them.
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Knowledge Hut
JANUARY 18, 2024
Data science provides several job roles with high salaries. Data Scientist-(average salary: Rs 11 lakhs, can reach up to Rs 25 lakhs) Data analyst-(average salary: Rs 4.2 lakhs) Data architect-(average salary: Rs 23 lakhs, can reach up to Rs 38.5 lakhs) Data engineer-(average salary: Rs8.1
Knowledge Hut
JUNE 23, 2023
You must develop predictive models to help industries and businesses make data-driven decisions. Steps to Become a Data Engineer One excellent point is that you don’t need to enter the industry as a data engineer. Data warehousing to aggregate unstructured data collected from multiple sources.
AltexSoft
JUNE 29, 2021
This article will focus on the role of a machine learning engineer, their skills and responsibilities, and how they contribute to an AI project’s success. The role of a machine learning engineer in the data science team. The focus here is on engineering, not on building ML algorithms. Who does what in a data science team.
Knowledge Hut
NOVEMBER 19, 2023
How to become: Get a degree in computer science or any other related field, master big data technologies such as HD and SRK, and be involved in real-world data projects. Job Titles That Follow: Positions like Big Data Engineer, Data Architect, Data Scientist etc.
Airbnb Tech
NOVEMBER 3, 2020
These investments centered around addressing areas related to ownership, data architecture, and governance. Ownership Prior to the Data Quality Initiative described in this post, data asset ownership was distributed mostly among product teams, where software engineers or data scientists were the primary owners of pipelines and datasets.
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