42 Data Architect Interview Questions with Answers + Guide in 2025

As distributed data sources grow and centralized models face limitations, 43% of companies now emphasize redesigning their data architecture as a modernization strategy. Creating data architectures with virtualizations and distributed data pipelining for better efficiency has become critical. These prospective approaches aim to improve scalability, adaptability, and access to diverse datasets, enabling organizations to handle modern complexities more effectively.

As a data architect, your expertise is integral as companies embrace modern practices. Your technical and behavioral skills are essential for organizations that face challenges with legacy ETL pipelines and centralized models. However, the glamorous role of a data architect comes with an obstacle called an interview.

In this article, we’ll cover essential data architect interview questions to help you prepare effectively for the role. Additionally, we’ve included valuable insights on the interview process and salary details in the final section, so be sure to check it out for a comprehensive overview.

Data architects are like designers for a company’s information system. They make sure data is stored, organized, and easy to access. Additionally, they design and manage the structure of an organization’s data systems to ensure scalability, efficiency, and accessibility. As a data architect, your responsibilities would include:

1. Data strategy: They collaborate with different teams and business stakeholders to understand the company’s vision and create strategies aligning with its goals.
2. Data modeling and integration: A major part of this position involves creating models that provide insights into how data should be structured, stored, and distributed in the company’s systems. Data architects also focus on designing unified structures that retrieve information from different sources and store it in one centralized unit.
3. Data governance: When designing systems, they take into account data quality, security, and compliance.

You would also be expected to collaborate with stakeholders, especially data engineers, to align data strategies with business goals and oversee technical teams to implement architectural solutions.

The relationship between data architects and data engineers is symbiotic. Data architects focus on the high-level design and structure of data systems, ensuring they align with business needs, while data engineers build and maintain the infrastructure to make that design work in practice. Data architects provide the blueprint, and data engineers handle the technical execution, ensuring the information efficiently flows when needed.

1. What would your current manager say about you? What constructive criticisms might he give?

Solution: Reflect on key strengths and areas for improvement. Discuss feedback related to your work ethic, communication, and technical skills. Mention how you’ve acted on constructive criticism to improve.

2. Tell me about a time when you exceeded expectations during a project. What did you do, and how did you accomplish it?

Solution: Share a specific example where you delivered beyond expectations. Highlight your steps to understand the project, innovate, and exceed goals.

3. Tell me a time when your colleagues disagreed with your approach. What did you do to bring them into the conversation and address their concerns?

Solution: Describe a situation where you faced disagreement. Show how you used active listening, communicated clearly, and collaborated to resolve differences.

4. How do you prioritize multiple deadlines? Additionally, how do you stay organized when you have multiple deadlines?

Solution: Discuss strategies like time management tools (e.g., task lists, calendars) and breaking down complex tasks to meet multiple deadlines.

5. How would you approach designing data architecture for a complex project?

Solution: Focus on understanding business needs, creating scalable and flexible designs, selecting the right technologies, and collaborating with stakeholders.

6. Can you describe a situation where you handled conflicting requirements on a project?

Solution: Prioritize stakeholder communication, consider trade-offs, and ensure the project’s goals are aligned. Propose compromises and communicate effectively.

7. How would you present data insights to stakeholders?

Solution: Use clear, concise visuals (charts, graphs), avoid jargon, and tailor insights to the audience’s needs. Engage stakeholders by focusing on actionable insights.

8. How can you calculate the first touch attribution for each user_id that converted, based on the attribution and user_sessions tables?

Solution:

Join attribution and user_sessions by user ID, then filter for conversion (conversion = TRUE). Sort the sessions by their timestamp to find the first occurrence of a conversion. Select the channel associated with that first session and return it for each user.

9. How can you extract the second longest flight between each pair of cities, considering both directions as the same pair, from the flights table and order the results by flight id in ascending order?

Solution:

Use a JOIN or UNION to treat flight pairs as bidirectional (same city pair), then use ROW_NUMBER to rank flights by duration for each city pair. Filter for the second rank and sort by flight_id in ascending order.

10. How can you write a query to determine the percentage of users who held the title of “data analyst” immediately before holding the title “data scientist,” with no other titles in between, from the user_experiences table?

Solution:

Use a JOIN on the user_experiences table, filtering for consecutive job titles. The query should ensure no other titles exist between “Data Analyst” and “Data Scientist”. Calculate the percentage by dividing the number of valid transitions by the total number of users.

11. How can you write a query to calculate the total three-day rolling average for daily deposits from the bank_transactions table, ensuring the output is formatted as ‘%Y-%m-%d’ for the date?

Solution:

Use a window function OVER to calculate a 3-day rolling average for each transaction. Ensure the PARTITION BY clause groups by the date and calculates the average for each day within the window. Format the date in '%Y-%m-%d'.

12. How can you write a query to find the five lowest-paid employees who have completed at least three projects, considering a project as completed when the End_dt is not NULL, based on data from the employees and projects tables?

Solution:

Use a GROUP BY on employee ID and a HAVING clause to filter employees who have completed at least three projects (check if End_dt is not NULL). Then, sort by salary and select the five lowest-paid employees.

13. How can you write a query to determine if each user has a subscription date range that overlaps with any other completed subscription, where a completed subscription is one that has an end_date recorded, based on the subscriptions table?

Solution:

Use a JOIN on the subscriptions table where the end_date is not NULL. Compare the date ranges to identify overlapping periods (e.g., using BETWEEN or range comparisons) and flag those overlaps.

14. How can you write a query to create a new table that tracks each student’s scores for exams 1, 2, 3, and 4, based on the exam_scores table, where missing exams are represented as NULL?

Solution:

Use CASE statements to create new columns for each exam (1, 2, 3, 4). Then, pivot the exam_scores table based on the exam ID, ensuring missing scores are represented as NULL.

15. How can you write a query to create a report that displays which shipments were delivered to customers during their membership period and includes a column is_member with values ‘Y’ if the shipment was within the membership period and ‘N’ if it was outside, based on the customers and shipments tables?

Solution:

Use a JOIN between customers and shipments based on user_id. Add a CASE statement to check if the shipment falls within the customer’s membership period (between membership_start_date and membership_end_date). Flag the result with ‘Y’ or ‘N’.

16. How can you write a query to identify customers who placed more than three transactions each in both 2019 and 2020, based on the transactions and users tables?

Solution:

Use GROUP BY on customer_id and filter using HAVING to select customers who have placed more than three transactions in both 2019 and 2020. This can be done by filtering on transaction dates and using the COUNT function to ensure a minimum of three transactions per year.

17. How can you write a query to return the two students with the closest SAT test scores, including the score difference? If there are ties, select the pair with the alphabetically higher names based on the scores table.

Solution:

Self-join the scores table to compare each student’s SAT score against all others. Calculate the absolute difference in scores, then use ROW_NUMBER or RANK to select the pair with the smallest difference. For ties, sort by student names alphabetically.

18. Write a function that generates a timeline of friendships, including both the start and end dates, by using two lists: one for when friendships were created (friends_added) and one for when they were ended (friends_removed). The function should track each pair of users’ friendship dates and only output the periods when a corresponding friendship was removed.

Solution:

To track friendships, create a mapping between user pairs and their friendship start date using friends_added. Then, for each entry in friends_removed, find the corresponding pair and record the end date. Output each pair’s timeline by joining the friends_added and friends_removed data and ensuring the friendship period is accurately reflected in the final result.

19. Write a function that calculates the probability of rain on the nth day after today, given the probability of rain depends on whether it rained today and yesterday. The probabilities are: 20% if it rained both days, 60% if it rained only one of the days, and 20% if it didn’t rain either day. The function should calculate this for any given day n after today.

Solution:

For each day, check the rain status for both today and yesterday. If it rained both days, the probability is 20%. If it rained on one day, the probability is 60%, and if it rained on neither day, the probability is 20%. Iterate through the days, applying these probabilities to simulate and calculate the rain status for the nth day.

20. Write a function to simulate two computing jobs running between 7 pm and midnight each night. If they overlap, they cause $1000 in downtime. The function should estimate the annual cost of this problem by simulating the overlaps for multiple nights and outputting the total cost.

Solution:

Simulate two jobs running each night. Generate random start times, then check for overlap by comparing their schedules. If there’s an overlap, calculate a $1000 downtime. Multiply the cost by 365 to get the annual downtime cost.

21. Write a function that returns a list of all prime numbers up to a given integer N. The function should return an empty list if there are no prime numbers less than or equal to N.

Solution:

Loop through all numbers from 2 to N, checking if a number is divisible by any number less than or equal to its square root. If a number isn’t divisible, it’s a prime number. Return all prime numbers as a list.

22. Write a function rotate_matrix that takes a 2D array and rotates it by 90 degrees in the clockwise direction.

Solution:

To rotate a matrix by 90 degrees, transpose it (swap rows and columns), then reverse each row. This in-place transformation ensures the matrix is rotated clockwise by 90 degrees.

23. Write a function normalize_grades that takes a list of tuples with names and grades and normalizes the grades to a linear scale between 0 and 1.

Solution:

For each student’s grade, subtract the minimum grade from the score and divide by the range (max-min). This scales all grades between 0 and 1, making them comparable on a normalized scale.

24. Write a function to get a sample from a standard normal distribution.

Solution:

Use Python’s random.normalvariate() method to generate random samples from a standard normal distribution, which gives values with mean 0 and standard deviation 1.

25. Write a function to calculate the standard deviation for each list of integers in a list of dictionaries and return a dictionary with the standard deviations for each list.

Solution:

For each list of integers, calculate the mean, then compute the variance by averaging the squared differences from the mean. Finally, take the square root of the variance to get the standard deviation.

26. Write a function to find all combinations of integers from a list that sum up to a given value N. The function should return a list of lists, where each inner list contains a valid combination of numbers.

Solution:

Use recursion or backtracking to find all unique combinations of integers in the list that sum to N. Store the combinations and return them as a list of lists.

27. Write a function to merge two sorted lists into one sorted list by combining their elements in order.

Solution:

Use two pointers to iterate through both lists. At each step, compare the current elements from both lists and append the smaller one to the result list. Continue until all elements from both lists are processed.

28. Write a function in pandas that calculates the cumulative percentage of students with test scores within specific score buckets: <50, <75, <90, and <100, for each grade level. The function should return a DataFrame with the grade, score bucket, and the percentage of students falling within each bucket.

Solution:

For each grade, classify students’ test scores into predefined buckets (<50, <75, <90, <100). Using pandas, group students by grade, then calculate the cumulative percentage of students falling into each score bucket.

29. Write a function to reorder a list of flight tickets, given a list of flights with starting and ending cities, so that the trip is reconstructed in the correct order, including layovers.

Solution:

To reorder the flight tickets, create a map of destination cities to their origin cities. Use this mapping to reconstruct the trip in the correct order, ensuring that layovers are appropriately placed between consecutive flights.

30. Write a function that finds the missing number in an array of integers, where the array contains numbers from 0 to n with one missing. The solution should have a time complexity of O(n).

Solution:

Calculate the sum of numbers from 0 to N using the formula N×(N+1)/2N, then subtract the sum of the elements in the array from this value. The difference will give the missing number.

31. Say you are tasked with designing a data mart or data warehouse for a new online retailer. How would you design the system?

Solution:

Design the system by focusing on a star or snowflake schema. The fact tables will include sales, returns, and inventory, while dimension tables will include products, customers, stores, and time. Use a data mart approach to focus on specific areas (e.g., sales), optimizing for analytics queries.

32. Say you work for an e-commerce website that receives clickstream data from Kafka on a daily basis. You’re asked to design a data analytics solution for storing and querying raw data, with a two-year retention period. The current data volume is around 600 million events daily. What kind of data analytics solution would you design, keeping costs in mind?

Solution:

Use a distributed storage system like Hadoop or S3 for raw data storage. For querying, utilize Amazon Redshift or Google BigQuery with an ETL process for aggregation. Use partitioning strategies based on time (e.g., day or hour) to optimize query performance. Ensure data is compressed to minimize storage costs.

33. Write a query to return the total number of vacation bookings in the last 90 days, last 365 days, and overall, based on a bookings table. Assume today is January 1st, 2022.

Solution:

Write SQL queries using COUNT and CASE statements to calculate bookings within the last 90 and 365 days. Use the CURRENT_DATE function to calculate date ranges and group results by the timeframe.

34. Let’s say you work as a data scientist at DoorDash. You are tasked to build a machine learning system that minimizes missing or wrong orders placed on the app. How would you go about designing this system?

Solution:

Use machine learning to build a prediction model for order placement errors. Incorporate features such as user history, order type, time, and location. Continuously evaluate and improve the model using metrics like accuracy and precision.

35. Let’s say you’re setting up the analytics tracking for a web app. How would you create a schema to represent client click data on the web?

Solution:

Design a schema with a table for clicks that logs user_id, timestamp, page_url, session_id, and click_action. Use a session table for tracking user sessions and a pages table for URL metadata.

36. Let’s say you work as a data architect at Facebook. Facebook is trying to transition its product from just doing likes on posts and comments to adding the multi-reaction under the like button. How would you approach this problem? What would the database modifications look like?

Solution:

Add new fields in the reactions table to support multiple reactions. Modify the UI to handle multiple reactions, updating the schema to track various reaction types and their counts.

37. Design a database schema for a restaurant review app with tables for users, restaurants, and reviews.

Solution:

Create users, restaurants, and reviews tables with foreign key relationships. Users table has user_id, name, and contact info. Restaurants table includes restaurant_id, name, location. Reviews contains review_id, rating, text, and links user_id and restaurant_id.

38. What are the product requirements for predicting the number of daily transit riders of the New York City Subway on an hourly basis, using hourly data from the client’s database as training data for an AI model?

Solution:

Collect hourly data on transit ridership, then use time series modeling (e.g., ARIMA, LSTM) to predict ridership for each hour based on historical data. Focus on real-time predictions and incorporate weather, events, and holidays as features.

39. How would you build a machine learning system to generate Spotify’s Discover Weekly playlist?

Solution:

Build a recommendation system based on collaborative filtering (user-user or item-item). Use content-based filtering for new music recommendations. Apply matrix factorization techniques like SVD to generate personalized playlists.

40. You are tasked with keeping track of customer addresses in your database. However, customers’ addresses change whenever they move. We want to keep track of their moving history as well as those who move in afterward. How would you create or modify a schema to keep track of these address changes?

Solution:

Use an addresses table with fields for customer_id, address, move_in_date, and move_out_date. Add a tenant_history table to track previous tenants. Use foreign keys to maintain historical data.

Here are some data architect case study questions:

41. How would you design a classifier to predict the optimal moment for a commercial break during a video?

Solution:

Let’s start out by clarifying the question. How exactly would you determine the “optimal moment” for a commercial break?

Since commercials are designed to build brand awareness and generate demand for a specific product, we could say that optimality is determined by how effective the placement of the video ad is. What are some metrics we could use to measure this?

42. Let’s say you have analytics data stored in a data lake. An analyst tells you they need hourly, daily, and weekly active user data for a dashboard that refreshes every hour. How would you build this data pipeline?

Solution:

Let’s start off by stating our functional requirements. Our solution must:

• Count the number of distinct users
• Display the data in the dashboard
• Show the distinct users in the past hour, day, and week in the data output

The interview process for data architects usually consists of five main stages.

Phone Screening: The first part of this process consists of a phone screen that generally takes 30–45 minutes. During this interview, the recruiter will ask you about your qualifications and educational background, as well as previous work experience.

Technical Interview: In this stage, your technical skills will be evaluated. You’ll need to work through a variety of data-related questions and problems, design data models, and/or complete some programming tests in Python, R, or SQL. For some companies, this could also include a whiteboard session.

Panel Interview: This interview is conducted with a group of interviewers, which could include other data architects or positions that work closely with the role. You’ll likely be asked a mix of behavioral and technical questions to assess your approach to designing data models and your problem-solving abilities.

Case Study Interview: Some companies have an additional case study interview to evaluate your ability to work through a real-world situation to either create a new data model or improve a pre-existing architecture.

Final Interview: In the final stage, you’ll meet with the senior team and leadership to discuss the long-term goals of the company and whether your vision aligns with their values.

Every organization has a unique interview process. Some companies have an interview process with fewer stages, while others will include more assessments to gauge your technical ability.

Here’s a brief list of key skills for a data architect:

1. Data Modeling: Expertise in creating conceptual, logical, and physical data models.
2. Database Design: Strong knowledge of RDBMS and NoSQL systems.
3. SQL Expertise: Advanced skills in writing complex queries and query optimization.
4. ETL Processes: Proficiency with ETL tools and custom scripting.
5. Cloud Platforms: Familiarity with cloud data services (e.g., AWS, Azure, Google Cloud).
6. Big Data Technologies: Experience with Hadoop, Spark, and data lakes.
7. Performance Tuning: Skills in indexing, partitioning, and query optimization.
8. Data Governance & Security: Understanding of data privacy, compliance, and security best practices.
9. Data Warehousing: Knowledge of data warehousing concepts and tools (e.g., Snowflake, Redshift).
10. Data Integration: Ability to integrate and transform data from multiple sources.

These skills are essential for managing and optimizing an organization’s data infrastructure effectively.

This guide has hopefully provided some helpful information to support you during the data architect interview process. Other details to focus on during your preparation include:

• Company knowledge: Research the company to learn more about its products and services, as well as any potential data-related challenges it’s currently facing.
• Fundamentals: Refresh your knowledge of key data architecture concepts, including database design and data modeling, integration, and warehousing.
• Best practices: Review common data architecture patterns, such as snowflake schemas, data lakes, dimensional modeling, and real-time processing.
• Data governance: Be prepared to talk about managing data quality, privacy, and security to protect the data architecture within an organization. Familiarize yourself with compliance regulations like GDPR and CCPA, encryption, and access control.
• Data modeling: Brush up on different data modeling techniques, including entity-relationship (ER) modeling and dimension modeling. Make sure you know the difference between OLTP and OLAP systems, as well as normalization and denormalization.