Salesforce Data Engineer Interview Questions + Guide 2024

Generating just shy of $35 billion in revenue for FY24, Salesforce has shown a remarkable and consistent growth trajectory since its inception in 2005. Salesforce is a leading customer relationship management platform (CRM) that helps businesses manage interaction with customers and prospects throughout the sales lifecycle.

Depending on the role and seniority, data engineers at Salesforce are responsible for understanding and working with Salesforce’s object model, managing data migration from both internal and external sources, and building real-time analytics pipelines.

You, as a candidate at Salesforce, have come to the right place to unravel details about the interview process and recurring interview questions for the data engineer role.

Salesforce emphasizes assessing your experience, passion, and ability to handle challenges—both technical and behavioral—during the data engineer interviews. It’s generally rigorous and designed to assess your cultural fit, problem-solving abilities, and technical skills. Here is how a typical data engineer interview at Salesforce goes:

Initial Screening Rounds

The process usually begins with a call with a recruiter. This stage is focused on your background, experience, and interest in the role. The recruiter will also discuss the role’s requirements and may ask some basic pre-defined technical questions.

If you pass the recruiter screen, you might have a conversation with the hiring manager as a second screening round. This discussion might dive deeper into your experience, the projects you’ve worked on, and how your skills align with the team’s needs.

Technical Assessment Round

In this round, expect to complete a coding challenge, either online or as part of a technical phone interview. This assessment will test your programming skills and your ability to solve data-related problems.

This stage often includes problem-solving questions that assess your knowledge of data structures, algorithms, and coding skills. You might also be asked about your experience with data pipelines, ETL processes, and databases. Case study questions might also be included in this round.

Onsite or Virtual Interviews

During the onsite or virtual round, your interviewer will deep dive into your technical abilities. You’ll be given problems to solve on the spot, often involving SQL queries, data modeling, and system design.

Salesforce data engineer interviewers will ask you to walk through your past projects and explain your approach to challenges.

You might also be asked to design a data pipeline or a database system. This interview assesses your ability to architect scalable and efficient systems, taking into account factors like data storage, retrieval, and processing.

Salesforce places a strong emphasis on cultural fit as well. So you’ll have behavioral interviews that explore how you work in teams, handle challenges, and align with Salesforce’s core values.

Executive Interview

Sometimes, there might be a final interview with a senior leader or executive in the company. This interview often focuses on your career aspirations, how you envision your role at Salesforce, and your alignment with the company’s long-term goals.

Here are the most common questions that are asked in Salesforce data engineer interviews:

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

2. Tell me a time when your colleagues did not agree with your approach. What did you do to bring them into the conversation and address their concerns?

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

4. Tell me about a project in which you had to clean and organize a large dataset.

5. Describe a data project you worked on. What were some of the challenges you faced?

6. How do you query the largest salary by the department from the employees table?

7. How do you extract and return a list of unique values that occur only once in a given dictionary {string: number}?

8. How do you determine if all elements in a set are “ugly powers,” where an ugly power is defined as an ugly number (having prime factors only 2, 3, 5) multiplied by any positive integer k?

9. What are the functional and non-functional requirements for a database system designed to manage API keys, transactions, user details, and payment information for Swipe Inc.?

10. Write a query to return the total number of bookings in the last 90 days, last 365 days, and overall, assuming today is January 1, 2022.

11. Why is it standard practice to explicitly put foreign key constraints on related tables instead of creating a normal BIGINT field? When considering foreign key constraints, when should you consider a cascade delete or a set null?

12. Write a function to merge two sorted lists into one sorted list, and state the time complexity.

13. Write a query to create a metric that ranks queries by their search result precision, rounded to 2 decimal places.

14. How would you design a system to process and display real-time data, including persistent comments and interactive reactions, across multiple platforms like Instagram, Facebook, and WhatsApp?

15. How would you design a system to process and display real-time data for a unified commenting system with interactive features?

16. Let’s say you’re tasked with building the YouTube video recommendation algorithm. How would you design the recommendation system? What are important factors to keep in mind when building the recommendation algorithm?

17. How can you implement a pop_tail function that removes the tail of a doubly linked list in O(1) time, returning the updated head and tail as a list or None if the list becomes empty?

18. How would you design a real-time data pipeline to track and analyze customer interactions across multiple Salesforce channels (e.g., website, mobile app, call center) in near real-time? Consider factors like data volume, latency, and scalability.

19. How would you implement data governance policies to ensure compliance with regulations like GDPR and CCPA in a Salesforce environment? What specific measures would you put in place to protect sensitive customer data?

20. How would you integrate AI and machine learning models into a Salesforce data pipeline to improve lead scoring, customer segmentation, or predictive analytics? Consider challenges like data quality, model deployment, and maintenance.

Preparing for a Salesforce data engineer interview requires a combination of technical knowledge, problem-solving skills, and understanding of Salesforce-specific concepts. Here are some key areas to focus on:

Understand the Role and Company

Gain a competitive edge by learning more about the company and the role. Start by thoroughly reviewing the job description. Understand the specific skills and experiences Salesforce is looking for, such as proficiency in SQL, data modeling, ETL processes, and familiarity with cloud platforms like AWS or Azure.

Introduce yourself to Salesforce’s data products and services, like Salesforce Einstein Analytics or Tableau. Knowing how Salesforce utilizes data engineering in its ecosystem will give you context and help you tailor your responses for the data engineer interview.

Strengthen Your Technical Skills

A data engineer is the bridge between data analytics and engineering. Therefore, you need to understand the concepts of data warehousing and data lakes and be familiar with tools like Redshift, Snowflake, or Databricks. Understand ETL processes and data pipeline designs.

Also, be ready to discuss your experience with building, optimizing, and maintaining data pipelines. As a data engineer, have a strong understanding of SQL and NoSQL databases, including relational databases.

Furthermore, understand concepts like Hadoop, Spark, and Hive, and be able to discuss their use cases. Also, be proficient in programming languages like Python, Java, or Scala, which are commonly used for data engineering tasks.

Practice Problem-Solving and Product Sense Questions

Focus on real-world problems that are relevant to data engineering. Practice solving data engineering problems from datasets and be prepared to discuss your approach and thought process. Your interviewer will also expect you to be able to communicate technical concepts clearly and effectively, both verbally and in writing.

You would also be given the opportunity to showcase your critical thinking abilities through product sense questions.

Appear in Mock Interviews

Conduct mock interviews with other candidates or AI Interviewers to get feedback on your performance and identify areas for improvement.

What is the average salary for a Data Engineer role at Salesforce?

The salary for a Data Engineer at Salesforce can vary significantly based on several factors, like location, experience, and specific role. The average base salary for a data engineer at Salesforce revolves around $134K, with total compensation averaging $281K in bonuses and shares.

What other companies are hiring data engineers besides Salesforce?

Many tech companies, both large and small, are actively hiring data engineers to support their data-driven initiatives. Some prominent examples include Amazon, Google, and Microsoft.

Does Interview Query have job postings for the Salesforce Data Engineer role?

Yes, we frequently post company job postings on our Job Portal. However, be also updated through the Salesforce Career Page to seek more recent job postings.

Preparing for a Salesforce Data Engineer interview requires a strong foundation in data engineering principles, coupled with a deep understanding of Salesforce-specific concepts. By focusing on technical skills, Salesforce-related knowledge, problem-solving, and communication, you can increase your chances of success.

Beyond the Data Engineer role, Salesforce also hires for positions including Data Analyst, Data Scientist, and Software Engineer.