Data Architect Interview Questions

Data Architect Interview Questions

Everything you need to know about hiring a Data Architect

Why hire a Data Architect?

Blend and churn data management, data warehousing, and data modeling and you will get a Data Architect. Why are Data Architects so popular?

Because the Future belongs to Data. As a population that generates 2.5 quintillion data bytes every day, it’s no surprise that it needs to be optimized and driven towards revenue growth.

As experts in creating data blueprints, Data Architects work across a variety of industries ranging from the technology sector, entertainment, and health care, to finance, and government as data is imperative in every business.

The leadership role is vital in conceptualizing and visualizing data frameworks. They are generally hired by C-suite executives who look for traits and goals that match their business objectives. 

Our tech-hiring guide tells you what exactly tech recruiters must look for in a Data Architect’s job role.

What is a Data Architect? 

The Data Management Body of Knowledge defines a Data Architect as one who develops a common business vocabulary across the business enterprise, establishes strategy-driven data requirements, and draws out advanced integrated designs that align with these requirements. 

They also ensure that enterprise strategies and the related business architecture are seamlessly aligned with each other.

In the words of Rob Byron, VP at Keystone Partner and former IT consultant,

“Data architects should evangelize best data practices to the technology team and socialize those practices within the businesses as well.”

On any given day, the role of a data architect reviews skills, designs, and analysis of data infrastructure, besides planning for future databases and implementing solutions to store and manage data for organizational needs and requirements.

Recommended Read: How to Hire Quality Talent

Why are Data Architects  in high demand?

Big data is only getting bigger. A combined study by Google and Harvard Business Review (HRB) revealed that most companies admit that democratized data access and democratized analytics are crucial for business success and sustainability. 

With data architecture, especially cloud-based, this trend is increasing exponentially in 2022.

As an important liaison between business and technology, data architects provide a standard common business vocabulary, express strategic requirements, outline high-level integrated designs to meet those requirements and align with enterprise strategy, and related business architecture. 

According to the U.S Bureau of Labor Statistics, careers in data architecture are projected at a growth rate of 8% between 2020 and 2030. It means there are close to 14,000 job openings per year in this field on average over the decade.

Average pay for Data Architect

As per Glassdoor estimates, the national average for a Data Architect’s salary in the USA is $1,18,868 per year, with an added compensation between $2,712 – $44,765.

Data Architect KPIs:

KPIs do not just track data hygiene but spotlight KRIs (Key Risk Indicators) as a good Data Architecture practice. 

Here are a few Data Architect KPIs for your perusal.

  1. Data Architecture Capability
  2. Measurement iterations
  3. Alignment of Metrics to Standards and Guidance
  4. Percentage of data movement via a standard tool
  5. Reduced data storage cost
  6. Translation of Data Value into Business Value

Related Read: How to hire a Data Security Analyst

Data Architect Job Description

Data Architects must be super qualified in computer and networking skills. Also, certifications from the Data Science Council of America (DASCA) are a valuable asset.

A typical Data Architect’s Job Description is like this.

  1. Design and develop data growth, analysis, and storage strategies for the company
  2. Support database requests in DB2, Teradata, Oracle, or SQL Servers
  3. Review SQL periodically for potential performance improvements and scope
  4. Guide data modeling efforts on storage technologies like HBase, Cassandra, etc
  5. Research and innovate with emerging open source storage technology stacks 
  6. Assist in ETL processes moving data through various DB platforms via custom-coded management applications
  7. Build and execute database applications using SQL Server Integration Services (SSIS)
  8. Create diagram deliverables through data modeling (conceptual, logical, and physical) for supported applications and projects
  9. Use ERWin to build logical data models from functional specifications, data requirements, and business rules provided by customers and clients
  10. Excellent understanding of data governance principles

Data Architect Interview Questions

1) Walk us through the fundamental skills of a Data Architect

2) What is a Cluster analysis? What purpose does it serve?

3) Differentiate between View and Materialized view

4) What is meant by Integrity constraints? What are its different types?

5) Should a data architect monitor and enforce compliance standards? What is the necessity?

6) Explain the different data models

7) How do OLAP and OLTP differ from each other?

8) What are the striking differences between a data scientist and a data architect?

9) What is your understanding of data architecture?

10) Explain the concept of virtual data warehousing

Recommended Read: Your Ultimate Guide to Hire Quality Talent

Best Practices for hiring Data Architects

As a senior-level professional,  a Data Architect works on a wide variety of data both on the cloud and site. The niche role is one of the most in-demand careers in the field of Data Science and Analytics. 

Generally, senior tech recruiters source for Data Architects in their professional network for making the best hire. However, understanding different types of architects and their job description come a long way in hiring tech talent.

On the flip side,  a majority of the recruiters are still stuck in the age-old recruitment methods. That’s why hiring red flags like over-reliance on credentials rather than competencies and lack of advanced evaluation tools in skill assessments have severely limited the talent pool.

Recruitment software like Glider AI takes candidate evaluation to the next level. Through a structured and standardized process, interviews are made candidate-friendly and also accurately assess skills and competencies. Hiring is not only bias-free but evaluated on real-world scenarios as well.

 

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