Arvest Bank, a reputable financial institution with deep roots in the heartland of America, is known for its commitment to delivering exceptional banking services and fostering community growth. As of 2023, Arvest Bank continues to thrive with a strong presence in several states, offering a wide range of banking products, from personal and business banking to mortgage and wealth management services.

Embarking on a career as a Data Engineer at Arvest Bank involves harnessing your technical expertise to manage and optimize the data systems that support its vast operations. The role demands proficiency in data management, analytics, and the ability to develop solutions that drive insightful business decisions. Arvest Bank seeks candidates with robust experience in data engineering, including knowledge in SQL, ETL processes, and data pipeline construction.

This guide will navigate you through Arvest Bank’s interview process, share commonly asked Data Engineer interview questions, and provide valuable tips to ensure you are well-prepared. Let's dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Arvest Bank as a Data Engineer. Whether you were contacted by an Arvest Bank recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from Arvest Bank's Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Arvest Bank data engineering hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Arvest Bank Data Engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Arvest Bank’s data systems, ETL pipelines, and SQL queries.

In the case of data engineering roles, take-home assignments involving data extraction, transformation, and loading (ETL), as well as data modeling, may be incorporated. Apart from these, your proficiency against data warehousing concepts, API integrations, and scripting languages like Python or Scala may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at Arvest Bank's office. Your technical prowess, including programming and data engineering capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Data Engineer role at Arvest Bank.

Quick Tips For Arvest Bank Data Engineer Interviews

• Understand Arvest Bank’s Systems: Arvest Bank might have unique systems and processes. Make sure you have a grasp of general banking data systems and how you would apply your skills to optimize these.
• Be Data Solution-Oriented: Arvest Bank values how well you can integrate data solutions that drive business decisions. Brush up on your knowledge of data warehouses, ETL processes, and APIs.
• Highlight Financial Data Insights: Show your ability to derive meaningful insights from financial data. Be prepared to discuss how you've used data engineering to provide tangible business benefits in the past.

Typically, interviews at Arvest Bank vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: What's the time complexity?

• Write a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Write a query to get the top 3 highest employee salaries by department. Given the employees and departments table, write a query to get the top 3 highest employee salaries by department. The output should include the full name of the employee, the department name, and the salary, sorted by department name in ascending order and salary in descending order.

• Write a function to combine sorted integer lists into one sorted list. Given a list of sorted integer lists, write a function sort_lists to create a combined list while maintaining sorted order without importing any libraries or using the 'sort' or 'sorted' functions in Python.

• Write a function to swap nodes in a singly linked list. Given the head of a singly linked list represented as a ListNode, and two zero-indexed positions x and y, write a function swap_node which swaps the positions of nodes x and y and returns the new head. Note that you cannot simply swap the values of these nodes; you must swap these using pointer manipulation.

• How would you investigate a decrease in credit card payment amount per transaction? You work for a financial company and notice that the credit card payment amount per transaction has decreased. How would you investigate the cause of this decrease?

• How would you build a strategy to find the best small businesses to partner with? Your credit card company wants to partner with more merchants. You have 100K small businesses to reach out to but can only contact 1,000. How would you develop a strategy to identify the best businesses to target?

• What features would you include in a model to predict a no-show for pizza orders? Imagine you run a pizza franchise and face a problem with many no-shows after customers place their orders. What features would you include in a model to predict a no-show?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates the forest. Additionally, why would we use random forest over other algorithms such as logistic regression?

• How would you build a fraud detection model with a text messaging service for a bank? You work at a bank that wants to build a model to detect fraud on the platform. The bank also wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction, allowing the customer to approve or deny the transaction with a text response. How would you build this model?

• What is the relationship between PCA and K-means clustering? Explain the relationship between Principal Component Analysis (PCA) and K-means clustering.

What is the average salary for a Data Engineer at Arvest Bank?

Q: What is the role of a Data Engineer at Arvest Bank?

A: As a Data Engineer at Arvest Bank, you will be responsible for designing, constructing, and maintaining scalable data pipelines and architectures. You will work closely with data analysts and data scientists to ensure data integrity, availability, and performance, enabling the bank to make data-driven decisions.

Q: What skills and qualifications are required for the Data Engineer position at Arvest Bank?

A: The ideal candidate will have a strong background in software engineering and data management. Essential skills include proficiency in SQL, Python, and ETL processes, as well as experience with cloud platforms like AWS or Azure. A solid understanding of data modeling, data warehousing, and big data technologies is also highly beneficial.

Q: What does the interview process for a Data Engineer at Arvest Bank look like?

A: The interview process typically involves an initial recruiter screening, followed by one or more technical interviews that assess your problem-solving abilities, technical skills in data engineering, and your experience with relevant tools and technologies. There may also be a behavioral interview to evaluate cultural fit within the company.

Q: What can I expect from the work environment at Arvest Bank?

A: Arvest Bank offers a collaborative and inclusive work environment that values innovation, continuous learning, and teamwork. As a Data Engineer, you’ll be part of a dynamic team of professionals committed to leveraging data for business insights and customer satisfaction.

Q: How should I prepare for an interview at Arvest Bank?

A: To prepare for your interview, thoroughly research Arvest Bank's products and services. Brush up on your technical skills, particularly those relevant to the role such as SQL, Python, and cloud platforms. Practice common data engineering interview questions and scenarios using resources like Interview Query to ensure you're fully prepared.

Arvest Bank offers an engaging and dynamic environment for Data Engineers, keen on fostering innovation and excellence. If you want more insights about the company, check out our main Arvest Bank Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Arvest Bank’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Arvest Bank Data Engineer interview question and challenge. You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!