Data architects create blueprints for data management systems. After assessing a company’s potential data sources (internal and external), architects design a plan to integrate, centralize, protect and maintain them. However, they .
In the fast-evolving technological world of today, a Data Architect is the specialist responsible for aligning all IT assets and objectives of a business. Those who are thinking about pursuing this career should be fully aware that this position presupposes not only working with data, software, networks, and cloud services, but also an ability to correctly model how the infrastructure and its components align with business requirements.
It’s also important to understand the way implementation plan realizes the model in a day-to-day operation. It’s not only about in-depth technical knowledge, but also an ability to employ it in the context of the business scope of activities.
What makes a Data Architect special
Data Architects tend to work on the design and development of the architecture as well as the data model used for reporting and business solutions. Since he/she must collaborate with different App teams, this specialist is expected to fully understand the needs of clients, from different sectors, in order to customize the products to their needs. Further, highly skillful specialists usually demonstrates profound technical knowledge, especially on topics and tools like SQL, ETLs, and BI Databases.
Data Architect job requirements
Day by day, companies are getting more demanding when recruiting big data architects. It came to the point that some companies need data architects who are literally ‘ninjas’ mastering data modelling tools. This is why data architects are often senior-level employees with plenty of years in business intelligence under their belts.
So what are the most typical requirements for this position? Let's go through them together.
First of all, a potential candidate should have an ability to understand and communicate how big data drives a business (operationally or via fast management insights). Secondly, he/she must be able to work with highly diverse data coming from a wide variety of highly siloed systems.
Even more importantly, a successful data architect might be tasked with bringing together any or all of the following: human resources data, manufacturing data, web traffic data, financial data, customer loyalty data, geographically dispersed data — each of which may be tied to its own particular system, programming language, and set of use cases.
On the other hand, it’s of vital importance to have outstanding skills in big data tools and technologies, including Accumulo, Hadoop, Panoply, MapReduce, Hive, HBase, MongoDB, and Cassandra, as well as data modelling and mining tools like Impala, Oozie, Mahout, Flume, ZooKeeper, and Sqoop. Relevant programming languages include Java, Linux, PHP, and Python.
Finally, most companies appreciate some experience in designing and implementing large on-prem and cloud-based data warehouse solutions utilizing cluster and parallel RDMS and NoSQL architectures.
How do you become a good data architect?
- 1. Pursue a degree in computer science, computer engineering or a related field. Start with a in computer science, computer engineering or a related field. Coursework should include coverage of data management, programming, big data developments, systems analysis and technology architectures.
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2. Develop and grow in your technical and business skills from data mining to analytical problem solving. There are many books and many exercises that can help you improve your skillset. However, the best way to grow professionally is always to look for opportunities to apply the knowledge you already have and work on new challenges. If you know someone who is already working in this field, ask them if they can share some of their knowledge with you. And if you don't know such person, just log into your LinkedIn account and look for professionals who are willing to share some of their knowledge.
3. Consider additional certifications and further learning. IBM, Microsoft, MongoDB and Amazon Web Service are some of the most important providers of data architecture certifications. They offer competitive pricing compared to other options, though you should expect to invest at least 150-200$ per certification.
At Datumize, a data architect is mostly busy with data management projects and advising the business and tech teams in matters of data modelling and data architecture standards. That's why we believe data architects should have a “big picture” view of the data needs of the entire company, while showing a perfect understanding of the data quality issues that the organization faces.
By bridging the business and technology worlds from a data/information perspective, this specialist plays a critical role in determining architectural approaches for data environments and helps ensure that the data needs of the company are being met. Finally, the ideal data architect has the experience, knowledge and vision to facilitate company’s integration via the data layer.
Interested in joining Datumize team? Check our open positions,