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. In the fast-evolving technological world of today, Data Architect is a specialist responsible for aligning all IT assets and objectives of a business. A person, who’s about to pursue 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 Good Data Architect so Special?
Data Architect tends to work on the design and development of the architecture as well as the data model used for reporting and business solutions. Collaborating with different Apps team, this specialist is expected to fully understand the needs of clients, from different sectors, in order to customize the products to their needs. A highly skillful specialist usually demonstrates profound knowledge of SQL, ETLs, and BI Databases.
Special job requirements
Day by day, the companies are getting more demanding when recruiting big data architects. It came to the point that some companies need data architects who are literally like ‘ninjas’ in data modelling tools. Data architects are likely to be senior-level employees with plenty of years in business intelligence under their belts.
What about the most typical requirements for this position?
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 needs to know how to work with highly diverse data employed by a wide variety of highly siloed systems. Even more, 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. Apart from that, it would be great to have some experience in designing and implementing large on-prem and cloud-based data warehouse solutions utilizing cluster and parallel RDMS and NoSQL architectures.
So, how to become a good data architect?
Pursue a degree in computer science, computer engineering or a related field.
Start with a bachelor’s degree 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.
Develop and grow in your technical and business skills from data mining to analytical problem solving.
Consider additional certifications and further learning.
When working in Datumize, a data architect is mostly involved into data management projects and advising the business and tech teams in matters of data modelling and data architecture standards. In other words, a data architect should have a “big picture” view of the data needs of the entire company, as well as show a perfect understanding of the data quality issues that the organization faces. 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, an ideal data architect has the experience, knowledge and vision to facilitate company’s integration via the data layer.