What is a Data Architect? How to transition from an IT technician to a Data Architect?

By Robert Half on 19 January 2024

What is a Data Architect? How to transition from an IT technician to a Data Architect?

  • The role of a Data Architect 

  • Job duties of a Data Architect 

  • Skills required by Data Architects 

  • Which certifications will help you become a Data Architect? 

  • Transitioning from IT technician to a Data Architect 

With the rapid development of information technology and the integration of data and various industries, the amount of data has ushered in explosive growth. According to the Digital China Development Report, the scale of China's digital economy reached RMB50.2 trillion in 2022, accounting for 41.5% of GDP, and is an important engine for China's economic growth. However, as digital transformation accelerates, China has a huge shortage of Data Architects. According to the data from www.newjobs.com.cn, the number of job openings for Data Architects increased by 42.7% year-on-year in the first quarter of 2023. 

The Data Architect is the designer of an enterprise's data management and strategy, responsible for designing, building, and governing data models that meet the organization's strategy, translating business requirements into technical requirements, and defining data standards and principles. Data Architects are the leaders of technology decision-making in enterprises and play a crucial role in the success of digital transformation and innovation. 

Tasks and responsibilities of a Data Architect

The main tasks and responsibilities of Data Architects include data model design (45%), data architecture development (25%), data quality and system maintenance (15%), and team communication and collaboration (10%). 

  • Data model design: Based on business requirements and data characteristics, Data Architects design data flows, integrations, transformations, databases, and data warehouses that maintain data integrity, consistency, availability, and scalability. 

  • Data architecture development: Data Architects use data tools and technologies, such as databases, ETL, BI, big data, and cloud computing, to build, deploy, operate, and optimize data architectures to improve data performance, efficiency, and value. 

  • Data quality and system maintenance: Data Architects regularly assess and improve the data architecture, including data quality inspection, data governance specifications, data architecture documentation, and data architecture evolution, to maintain the adaptability, stability, and sustainability of the data architecture. 

  • Team communication and collaboration: Data Architects need to effectively communicate and collaborate with business units, data analysts, data scientists and other data-related roles in areas such as requirements analysis, solution analysis, problem-solving, and knowledge sharing, to improve data utilization and impact. 

Skills required by Data Architects:

  • Communication skills: Data Architects must have excellent interpersonal skills and strong collaboration and leadership skills to communicate and collaborate effectively with members of different departments, as well as to present visual data related to business objectives. 

  • Strategic thinking: Data Architects need to have a thorough understanding of the lifecycle of business procedures and system development, project management methods and testing techniques, and understand their long-term impact. 

  • Data analysis and innovation: Data Architects need to collect, organize, clean up, synthesize, and interpret data to turn it into valuable insights to inform decision-making. 

  • Data modeling and design: This is the core skill of a Data Architect and the most requested skill in job descriptions. Data Architects need to be proficient in mathematics and computer science, familiar with the basic concepts and methods of data modeling, and commonly used data modeling tools. 

  • Technical skills for data management: 

  • Database: Data Architects need to be proficient in at least one relational database and one non-relational database, such as Oracle, SQL Server, MySQL, MongoDB, and Redis, and related database languages such as SQL, PL/SQL, and NoSQL. 

  • ETL: Data Architects need to be skilled in using at least one ETL tool, such as Informatica, DataStage, SSIS, and Kettle, and related data transformation and cleaning technologies, such as data mapping, data verification, and data quality management. 

  • BI: Data Architects need to be skilled in using at least one BI tool, such as Tableau, Power BI, QlikView, and SSRS, as well as related data visualization and reporting technologies, such as data dashboards, data analytics, and data mining. 

  • Big Data: Data Architects need to be familiar with the basic concepts and frameworks of big data, such as Hadoop, Spark, Hive, Kafka, and Storm, as well as related data processing and analysis technologies, such as MapReduce, Spark SQL, Spark Streaming, and Spark MLlib. 

  • Cloud computing: Data Architects need to be familiar with the basic concepts and services of cloud computing, such as AWS, Azure, and GCP, as well as related data storage and computing services, such as S3, DynamoDB, RDS, EC2, and Lambda. 

Completing the following professional qualification certifications can help you become a Data Architect.

  • Data Architect certification: This is a professional certification offered by the International Data Management Association (DAMA) that assesses the knowledge and competence of Data Architects, including data architecture principles, methods, techniques, tools, standards, and best practices. There are two levels of certification, Certified Data Analyst Professional (CDAP) and Certified Data Analytics Specialist (CDAS). 

  • Database certification: The major database vendors provide certifications that assess the Data Architect's understanding and application of database design, development, management, optimization, security, etc. Common database certifications include Oracle certification, SQL Server certification, MySQL certification, and MongoDB certification. 

  • Big data certification: The major big data vendors provide certifications that assess the Data Architect's understanding and application of big data architecture, processing, analysis, visualization, etc. Common big data certifications include Cloudera certification, Hortonworks certification, IBM certification, and Google certification. 

  • Cloud computing certification: The major cloud computing vendors provide certifications that assess the Data Architect's understanding and application of the foundation, service, architecture, and security of cloud computing. Common cloud computing certifications include AWS certification, Azure certification, and GCP certification. 

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How to transition from an IT technician to a Data Architect?

If an IT technician is interested in becoming an outstanding Data Architect, he or she can start by learning the basic data architecture knowledge. After obtaining certificates or professional qualifications related to data architecture, he or she needs to accumulate work experience related to data architecture, and constantly update and expand his or her knowledge and expertise. 

  • Essential technical skills for learning data architecture: IT candidates can learn the basic concepts, data tools, and techniques of data architecture through self-study or training. 

  • Obtaining certificates or professional qualifications related to data architecture: IT candidates can choose suitable certificates or professional qualifications related to data architecture based on their interests and goals, such as Data Architect certification, database certification, big data certification, and cloud computing certification. 

  • Gaining work experience related to data architecture: IT candidates can start by gaining experience from jobs related to data architecture, such as data analysts, data engineers, and data scientists. IT candidates also need to continuously learn and practice data architecture design, implementation, assessment and communication skills at work, and collaborate effectively with business units and data teams to enhance their data architecture capabilities and value. 

  • Continuously learning and expanding knowledge and skills in data architecture: IT candidates should keep abreast of the latest developments and trends in data architecture, and constantly try and explore new areas and applications such as data governance, data ethics, data security, and data intelligence. 

With the expansion of the digitization process, the demand for Data Architects in enterprises is also increasing. The Data Architect is the overall designer of an enterprise's data strategy, responsible for building data models, developing data management strategies, and monitoring data quality and environment. It requires the Data Architect not only to have a solid background and experience in data technology, but also to have good communication, analysis and collaboration skills. If you are interested in becoming a Data Architect, please visit our website: https://www.roberthalf.cn/zh/jobseekers. We will provide you with professional consulting and recruitment services to help you achieve your career goals and dreams. 

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