How to become a Data Architect? | How to start career with Data Architect?

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Who is Data Architect?

Data Architect is the person who creates blueprints of the overall data management system. After knowing about companies internal and external data sources, a data architect designs a full proof plan to centralize, integrate, secure and scale data sources.

Why Data Architect is difficult job?

It is known to everyone that playing a job role as data architect is really a tough job. Because most of the company want to hire a data architect who are skilled in following techniques;

  • Data modeling techniques
  • Experts in data warehousing, ETL tools
  • Experts in SQL databases or data administration

If you see a job description of a data architect you will not be surprised to see an extensive list of technical skill a company is looking for and it will be something like this;

Technical Skills
  • Application server software (e.g. Oracle)
  • Database management system software (e.g. Microsoft SQL Server)
  • User interface and query software (e.g. IBM DB2)
  • Enterprise application integration software (e.g. XML)
  • Development environment software
  • Backup/archival software
  • Agile methodologies and ERP implementation
  • Predictive modeling, NLP and text analysis
  • Data modeling tools (e.g. ERWin, Enterprise Architect and Visio)
  • Data mining
  • UML
  • ETL tools
  • Python, C/C++ Java, Perl
  • UNIX, Linux, Solaris and MS Windows
  • Hadoop and NoSQL databases
  • Machine learning
  • Data visualization

Business Skills

  • Analytical Problem-Solving
  • Industry Knowledge
  • Expert Management
  • Effective Communication

That’s sort of the ideal case. That’s ideal, because then they actually know the infrastructure that’s involved. Actually, most data architects are senior-level person with plenty of years experience in business intelligence under their belts.

 Key Responsibilities for Data Architect

  • Develop data models for database structures
  • Design, document, construct and deploy database architectures and applications (e.g. large relational databases or NoSQL databases)
  • Create complete picture of how data will flow
  • Take care of technical functionality like scalability, security, performance, data recovery, reliability, etc.
  • Maintain a corporate repository of all data architecture artifacts

Sometimes, they collaborate with IT teams and management to devise a data strategy that addresses industry requirements to solve the problem.

What Kind of Degree Will I Need?

Degree Level Bachelor’s degree or Master Degree
Degree Field Computer science, computer engineering, information technology, or a related field
Certification Not required but can sometimes help with employment prospects and advancement
Experience 4-10 years of work experience in the Data Field

Do I Need Certifications?

It depends on you. If you want to hand pick some online courses and certifications to keep growing  your learning curves then you are always welcome. You can also try solving some real world data problem to gain knowledge on the other way.

As of 2015, there was no expert certification explicitly dedicated to data architects. There are, however, plenty of skill-specific credentials from vendors with a stake in data management (e.g. Oracle, Microsoft, IBM, AWS, Google etc.)

Again, that it really vary from organization to organization. Some want certified employees where as others believe in real world experience to solve the problem.  As I already mentioned,this is really a difficult job role because of organizations’ expectation from you. Some companies want data architects who are very good in data modeling techniques. Others need experts in data warehousing, ETL tools, SQL databases or data administration.

In a nutshell, a good data architect should have at least below knowledge:

  • Data Warehousing
  • ETL Tools like Pentaho, Talend, Informatica etc.
  • SQL Databases and NO-SQL Databases
  • Data Administration and Data modeling tools
  • Data Communication tools
  • Actually Data Architects are senior level employees having many years of experience in data field.