Wells Fargo Data Engineer Interview Guide

With a YoY increase of over 21% and total revenue of more than $123 billion in 2024, Wells Fargo is the third largest bank in the US, trailing only JPMorgan Chase and Bank of America. It offers a wide range of financial services, including banking, investment services, wealth management, and loans.

Data engineers at Wells Fargo specifically focus on building and maintaining the data infrastructure and pipelines that support the bank’s wide range of financial services. Managing and processing customer data, building pipelines to move data, and developing data infrastructures to store and process large volumes of data.

As a data engineer candidate for Wells Fargo, you’ve come to the right spot to get the inside scoop on the interview process and prepare for the data engineer interview questions that might come your way. So, let’s cut to the chase and jump right in.

Wells Fargo is pretty transparent about their interview process. Although they discuss a general outline, they don’t detail the specific interview process for data engineer roles. The interview process for a data engineer role at Wells Fargo typically involves multiple rounds, each designed to assess your technical skills, problem-solving abilities, and cultural fit. Here’s a general breakdown of what you can expect:

Initial Phone Interview

The process usually starts with a phone interview conducted by a recruiter or HR representative. This conversation focuses on your background, experience, and understanding of the role. You may also be asked basic questions about your resume, your interest in Wells Fargo, and your availability.

Technical Assessment Rounds

You may be asked to complete a coding challenge online or in-person to evaluate your technical skills and problem-solving abilities. This could involve tasks related to data structures, algorithms, or data manipulation.

If you pass the coding test, the next step may involve a technical phone interview with a data engineer or a member of the engineering team. This interview will dig deeper into your technical expertise, including questions about databases, ETL processes, data pipelines, and programming languages, especially Python.

Onsite Interview Loop

If you advance, you’ll likely be invited for a series of onsite or virtual interviews. These sessions usually include a deep dive into your technical skills, with whiteboard coding challenges, system design questions, and discussions about your experience with big data technologies like Hadoop, Spark, or Kafka.

Wells Fargo also places a strongly emphasise cultural fit, so expect a behavioral interview that will assess your soft skills, problem-solving abilities, and how you’ve handled challenges in previous roles.

Team Fit Interview

You may have a final round of interviews with potential team members or managers. This stage assesses how well you would fit within the specific team and may include discussions about the team’s projects, workflows, and expectations.

Depending on the role, a final interview with a hiring manager or senior leader might be conducted to discuss your long-term career goals, interest in Wells Fargo, and how you envision your role as a data engineer within the company.

Wells Fargo expects their data engineers to be proficient in algorithms, SQL, analytics, and have a basic understanding of product metrics. Here are some recurring questions that are often asked in Wells Fargo data engineer interviews:

1. What makes you a good fit for Wells Fargo?
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. Describe an analytics experiment that you designed. How were you able to measure success?
5. Describe a data project you worked on. What were some of the challenges you faced?
6. Write a query to display the number of users, transactions, and total order amount per month for the year 2020.
7. Given an employees and departments table, select the top 3 departments (with at least 10 employees) ranked by the percentage of employees earning over 100K.
8. Write an SQL query to select all columns with SQL from the flights table, which contains flight details for an airline.
9. What key factors would you consider when designing end-to-end ETL and reporting architecture for an e-commerce company expanding worldwide?
10. Write a function rectangle_overlap(a, b) to determine if two rectangles, each defined by four unordered corner points, overlap; return True if they do and False otherwise.
11. Write a function is_subsequence to determine if string1 is a subsequence of string2.
12. Create a function that returns a list of words that are not present in both input sentences, treating words as case-insensitive.
13. Let’s say you’re working on keyword bidding optimization. You’re given a dataset with two columns. One column contains the keywords that are being bid against, and the other column contains the price that’s being paid for those keywords. Given this dataset, how would you build a model to bid on a new unseen keyword?
14. Write a function get_last_page to return the last page number from a string of ascending integers, or the last number in order if the sequence is incorrect.
15. Using the annual_payments table, how would you write a query to count “paid” transactions with an amount ≥ 100? and the product with the highest revenue from “paid” transactions?
16. Write a query to find users who placed fewer than 3 orders or spent less than $500.
17. Let’s say we have 1 million app rider journey trips in the city of Seattle. We want to build a model to predict ETA after a rider makes a ride request. How would we know if we have enough data to create an accurate enough model?
18. Given a list of strings (sentences) containing poems, return a dictionary where the keys are word frequencies and the values are lists of words with those frequencies, with all words processed as lowercase.
19. Write a function, digit_accumulator(s), that returns the sum of all digits in the given floating-point number string.
20. We have two models: one with 85% accuracy, and one 82%. Which one do you pick?

Preparing for a Data Engineer interview at Wells Fargo requires a solid understanding of both technical and behavioral aspects of the role. Here’s how to do it:

Review Core Data Engineering Concepts

Brush up on fundamental data structures and algorithms that are often assessed in Wells Fargo data engineer interviews. This includes arrays, linked lists, trees, graphs, sorting, searching, and dynamic programming concepts. Make sure you’re comfortable with SQL querying, database design, and normalization. Understand how to write complex queries, optimize them, and work with different types of databases

Also be well-versed in Extract, Transform, Load (ETL) processes. Understand the tools and techniques used to move and transform data across different platforms. Consecutively, familiarize yourself with big data tools and frameworks like Hadoop, Spark, Kafka, and Hive. Know how these technologies are used in data processing pipelines.

Practice Coding Challenges

Participate in coding challenges and focus on problems related to data manipulation, sorting, and algorithmic challenges. Use online platforms and solve our Python Interview Questions to stay ahead of the competition.

Understand System Design

Your interviewers at Wells Fargo would expect to discuss how you would design a data pipeline from scratch. Include data ingestion, processing, storage, and retrieval while responding. Be ready to explain your choice of tools and technologies.

Understand how to design systems that scale and perform efficiently. Be prepared to discuss your experience optimizing data storage and processing times and ensuring data consistency.

Prepare for Behavioral Questions

Expect to be asked questions regarding your experience with data and the financial sector. Use the STAR method to structure your responses to behavioral questions. Wells Fargo values teamwork, problem-solving, and leadership, so be ready to discuss examples from your experience.

Research Wells Fargo and the Finance Industry

Gain a solid understanding of Wells Fargo’s business, especially its data-driven initiatives. Knowing how they leverage data can give you insights into what they might be looking for in a data engineer. Be prepared to demonstrate your understanding of data privacy regulations like GDPR and CCPA.

Moreover, discuss your experience working with large datasets and case studies related to financial transactions, customer information, and risk assessment. Also highlight your ability to build data pipelines for fraud detection, risk modeling, and compliance reporting.

Participate in Mock Interviews

Consider doing mock interviews with peers or using our AI Interviewer to simulate the interview experience. This will help you get comfortable solving problems under time constraints and pressure situations like Wells Fargo data engineer interviews.

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

The average salary for a Data Engineer at Wells Fargo can vary depending on factors such as location, experience level, and specific role responsibilities. However, based on recent data engineer salary data, you can expect somewhat around $115K in base salary and $96K in total compensations.

What other companies are hiring Data Engineers besides Wells Fargo?

Many technology companies, financial institutions, and consulting firms are actively seeking Data Engineers. Some well-known companies that frequently hire Data Engineers include Amazon, Microsoft, and JPMorgan.

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

Yes, we have job postings for the Wells Fargo data engineer role on our Job Board, but it’s always recommended to check specific company career pages to stay updated on the job postings.

Preparing for a Data Engineer interview at Wells Fargo requires a combination of technical proficiency, domain knowledge, and effective communication skills.

By focusing on key areas like data pipelines, cloud technologies, financial industry expertise, and problem-solving, you can increase your chances of success. In addition to Data Engineers, Wells Fargo offers a variety of other roles within the technology and data space, including Business Analyst, Data Analyst, and Data Scientist.