Top 10 Skills for Data Architects


Technical track career in Data Science such as Data Architect require years of experience and training coupled with knowledge of broad range of tools. The top 10 skills for Data Architects are as follows:

Business Skill

Data Architects should have vast knowledge of the industry, trends and competition so they can solve issues efficiently. Ability to provide data for business purpose to increase customer satisfaction, identification of key performance indicators, product improvement, business decisions on growth, diversification of services, expenditure evaluation and risk assessment evaluation.

Programming Skills like SQL, Python and Java

SQL (Structured Query Language) is a must have skill for Data Architects. SQL is used to query and manipulate data from relational database models. We have different types of SQL statements such as Data Manipulation Language (DML), Data Definition Language (DDL), Data Control Language (DCL) and Transactional Control Language (TCL).

DML: Select, Insert, Update, Delete

DDL: Create, Alter, Drop

DCL: Grant, Revoke

TCL: Commit, Rollback, Save Transaction

Python as a multi-purpose language can be used to develop several applications used in wide range for data analysis.

Java is a class-based, object-oriented, general programming language used to build dynamic applications used on Mobile, desktop, Web, and Server side.

Data Modelling

Source: Sketchbubble

Data modelling is an important skill. It shows the Architect understands the data model and design principles which enhance business processes. Understanding schema, entities, data flow, hierarchy are attributes of communication between Architects and data in their organization.

Applied Math’s and Statistics

Math’s and statistics are skills needed for Data Architect positions due to analytical reasoning, computation, interpretation and presentation of data to solve business problems thereby enhancing decision making processes.

Design Skills

Data Architects should have the ability to design models that bring solution for businesses and services for users. Data should be easily available to authorized users, and data elements should be well defined so that they are correctly interpreted. Data quality and integrity should be managed by various design techniques.

Machine Learning and Natural Language Processing

Knowledge of Machine Learning, Pattern Recognition and Natural Language Processing is very important because Data Architects understand interaction between computers and human language to resolve data driven problems. They also use clusters for handling data and text mining.  

Excellent Communication Skill

Data Architects should be able to communicate and influence their customers positively.

Databases and Cloud Architecture

Source: Thewindherald

Data Architects most part of the job is on the Cloud Infrastructure (Iaas, Paas, Saas). Understanding Cloud technologies such as Microsoft Azure, Google Cloud, Amazon Web Services (AWS) and Oracle Cloud is very important. Also, knowledge of NoSQL database is required as well as experience to handle data technologies thatsuch as; MongoDB, Hadoop, Cassandra and Pig, MapReduce and HBase.

Ability to use a variety of Design/Visualization tools

A good Architect is not limited to one toolset. A lot of design and visualization tools out there continue evolving and new ones possibly will be introduced in the future.

Creative and Analytical Problem Solving

This skill is among-st the top 10 skills for Data Architects. Becoming creative as well as analytical in resolving issues is a sought-after skill for Architect positions.

In Conclusion, the above listed skills if acquired, will make a great Data Architect. Remember these skills take some years to acquire, so have a set objective, keep learning and training to become an outstanding Data Architect.

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