How to become A Data Architect

• Enterprise Data Architect
• Cloud Architect
• Security Architect
• Machine Learning Architect
• Big Data Architect

What do Data Architects do?

A ​​Data Architect would typically need to:

• Design, employ, evaluate, and optimise efficient and analytical architectural strategies and platforms to store and retrieve big data as per business needs and to achieve competitive solutions
• Develop conceptual and logical flowcharts & data models 
• Install and configure information systems
• Optimise new and existing database systems; suggest solutions to migrate data from legacy systems to new generation systems
• Set up a logical framework for scalable data models for large applications
• Analyse the structural requirements to fulfil for incorporating new software & applications 
• Manage data according to organisational needs, changing database models and enterprise architecture
• Develop and implement suitable security and backup protocols
• Enhance system performance by testing, troubleshooting and incorporating new components
• Collaborate with other teams to identify future requirements and areas of improvement that will streamline data structures 
• Support Management Information Systems (MIS)
• Update yourself continuously with the latest industry tech stack

Data Architects spend most of their day in modern, well-equipped offices on their computers analysing information. They may also have to attend inquiry calls from clients.

As a Data Architect, you may need to travel to attend meetings, conduct presentations or training sessions, or set up and manage databases. 

Data Architects generally work regular business hours from 9 am to 5 pm and may put in more than 40 hours a week. Their schedules may vary depending on deadlines. If you are working on a freelance assignment, you may have the freedom to establish your work days and hours. 

Finding a new job might seem challenging. Data Architects can boost their job search by asking their network for referrals, contacting companies directly, using job search platforms, going to job fairs, leveraging social media, and inquiring at staffing agencies.

Data Architects are generally employed by:

• Data Processing Firms 
• Systems Design Services Firms 
• Insurance Companies 
• Banks 
• Retail Companies 
• Healthcare Firms

Professional associations and organisations, such as the International Data Management Association (DAMA), are crucial for Data Architects interested in pursuing professional development or connecting with like-minded professionals in their industry or occupation. Membership in one or more adds value to your resume while bolstering your credentials and qualifications.

• Ensuring quality and reliability when dealing with diverse data; matching data formats and avoiding duplicate or missing data; preparing data for analysis
• Designing architecture right from the planning stage so that it can be scaled up with minimal impact on budget and performance
• Protecting data from fraudsters, hackers and other cyber criminals; securing perimeters; anonymising and encrypting data to take away sensitive elements  
• Collaborating with business teams to keep data architecture & strategies business-driven
• Ensuring that all employees understand the data and its purpose
• Complex corporate data environments due to various reasons, such as mergers & acquisitions which bring together disparate systems
• Adapting rapidly evolving methodologies, architecture and tools to suit changing corporate culture
• The imbalance between professional and personal life due to work pressures and long working hours to meet deadlines
• Health problems caused due to sitting down for long hours and working on computers

Any academic program that a potential Data Architect takes up typically requires a period of supervised experience, such as an internship. You may undertake internships in IT fields under the supervision of experienced Data Architects that enable you to master application architecture, network management, and performance management. Experience is particularly valuable since data architecture typically does not offer entry-level jobs.

Read about the profession and interview or job shadow experts working in data architecture to prove your commitment to course providers and prospective employers. 

Varying levels of qualifications are required for this role, depending on the employer. Most may be more concerned with prior experience and skills, whereas others may want formal qualifications.

Data Architects typically require a bachelor’s degree in computer science, computer engineering, information technology, or a related field. Such programs include understanding database languages, such as Structured Query Language (SQL), data management, programming, big data developments, systems analysis and technology architectures.

Some Data Architects may choose to pursue a master’s degree, particulary an MS (Master of Science) in computer science, information systems, or information technology, which employers value highly. An MS that focuses on data or database management may put you on the track to career progression, salary increase, enhanced professional reputation, and a wide network of contacts. 

Certification demonstrates a Data Architect’s competence in a skill set, typically through work experience, training, and passing an examination. When acquired from an objective and reputed organisation, it can help you stand out in a competitive job market, carry a significant salary premium of up to 18 per cent, increase your chances of advancement, and allow you to become an independent consultant. Successful certification programs protect public welfare by incorporating a Code of Ethics.

Some certifications that are highly valued across various industries include Certified Data Management Professional (CDMP) and Salesforce Certified Data Architect. To decide on an appropriate certification, you may seek help from your mentors or study job descriptions of various companies to find out about the latest trends. 

Performance, experience, and the acquisition of professional qualifications drive career progression. Employees with consistently high levels of performance may be eligible for promotion every two to three years. 

Data Architects may begin as Database Administrators. Having developed a high level of expertise in database management, data modelling and data warehousing, you may advance within the firm to become Data Architect, Senior Data Architect and then Lead Data Architect or Project Manager. This change will likely result in new challenges and responsibilities accompanying greater repute, leadership opportunities and sizable paychecks.

With adequate experience, you may take up freelance assignments.

Candidates with the necessary skills, relevant experience and a master’s degree in computer science or data science have the best job prospects. Relevant certification will enhance your employability.

Continuing professional development (CPD) will help an active Data Architect build personal skills and proficiency through work-based learning, a professional activity, 

formal education, or self-directed learning. It allows you to upskill continually, regardless of your age, job, or level of knowledge.

You will need to build familiarity and ease with the programming language that your enterprise uses. To stay abreast with evolving technology, you may consider taking in-person or online courses in data modelling techniques, data warehousing, ETL (extract, transform, load) tools, SQL (Structured Query Language), databases or data administration. Equipping yourself with professional certifications offered by companies such as IBM, Salesforce and Hortonworks will lend you a competitive edge in the job market. 

Data Architect vs Data Engineer

Data Architects are advanced data engineers. They design the blueprint of the organisational data management framework and data engineers later build the framework based on the blueprint. Data Architects visualise, design and prepare data within frameworks that data scientists, engineers or analysts can employ. Data engineers also help Data Architects with framework construction to enable data search and retrieval.

Data Architect vs Data Scientist

Data Architects convert business requirements into technical requirements and build the framework which data scientists then use to develop models by applying the concepts of computer science, mathematics and statistics.

Potential Pros & Cons of Freelancing vs Full-Time Employment

Freelancing Data Architects have more flexible work schedules and locations. They have full ownership of the business and can select their projects and clients. However, they experience inconsistent work and cash flow, which means more responsibility, effort and risk.

On the other hand, a full-time Data Architect has company-sponsored health benefits, insurance, and retirement plans. They have job security with a fixed, reliable source of income and guidance from their bosses. Yet, they may experience boredom due to a lack of flexibility, ownership, and variety.

When deciding between freelancing or being a full-time employee, consider the pros and cons to see what works best for you.

Over 1 million customers use Walmart every hour, and their transaction data is stored in databases that may contain more than 2.5 petabytes of data.

Data architecture is currently one of tech’s fastest-growing sectors. The role of a Data Architect is high-profile and earned through years of dedicated work. Data Architects enjoy high job satisfaction and varied creative challenges. They work with ever-evolving technologies to generate data management blueprints that align with enterprise culture and short- and long-term business objectives.

Become an expert, an expert in anticipating and building the new skills you need to meet the demands of the future. Having specific technical skills such as Hadoop, Spark or data preparation for a specific business will improve your job prospects and reliability.