nCino, Inc. is a rapidly growing fintech company offering a cloud-based banking solutions platform that enhances efficiency, transparency, and profitability for financial institutions. Known for its innovative culture and cutting-edge technology, nCino serves numerous banks and credit unions, facilitating a seamless digital banking experience.

As a Data Engineer at nCino, you will play a crucial role in managing and optimizing their data infrastructure, ensuring data accessibility, integrity, and security. The position requires expertise in data warehousing, ETL processes, and proficiency with tools like SQL, Python, and modern data platforms.

This guide on Interview Query is designed to help you prepare for the nCino Data Engineer interview process. We’ll dive into the types of questions you can expect, provide insights into the interview stages, and share practical tips to increase your chances of success. Let’s get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining nCino, Inc. as a Data Engineer. Whether you were contacted by an nCino 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 the nCino 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 nCino Data Engineer 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 nCino 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 nCino’s data systems, ETL pipelines, and SQL queries.

In the case of Data Engineer roles, take-home assignments regarding database design, data integration, and data transformation are incorporated. Apart from these, your proficiency against coding, algorithm problems, and understanding of distributed systems 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 the nCino office. Your technical prowess, including programming and data architecture 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 nCino.

Quick Tips For nCino, Inc. Data Engineer Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your nCino interview include:

• Understand nCino’s Products and Market: Familiarize yourself with nCino’s suite of products and how they cater to the financial services industry. This will help you provide contextual, relevant answers during your interview.
• Master Data Engineering Concepts: nCino’s interview process for Data Engineers places a strong emphasis on data pipeline architecture, ETL processes, and SQL proficiency. Reviewing these concepts thoroughly can give you a significant edge.
• Cultural Fit and Team Collaboration: nCino values a collaborative culture. Be prepared to answer behavioral questions that demonstrate your ability to work well in team settings and your alignment with nCino’s core values.

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

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• 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: Determine the time complexity.

• Create a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Develop a function precision_recall to calculate precision and recall metrics. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. You are given a target value to search. If the value is in the array, return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with these results?

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to address this issue?

• Why would the number of job applicants decrease while job postings remain the same? You observe that the number of job postings per day has remained constant, but the number of applicants has been decreasing. What could be causing this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common problems in "messy" datasets.

• Is this a fair coin based on 10 flips resulting in 8 tails and 2 heads? You flipped a coin 10 times, resulting in 8 tails and 2 heads. Determine if the coin is fair based on this outcome.

• How do you write a function to calculate sample variance for a list of integers? Write a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. Example input: test_list = [6, 7, 3, 9, 10, 15]. Example output: get_variance(test_list) -> 13.89.

• Is there anything suspicious about an A/B test with 20 variants where one is significant? Your manager ran an A/B test with 20 different variants and found one significant result. Would you consider this result suspicious? Explain your reasoning.

• How do you find the median of a list where more than 50% of the elements are the same in O(1) time and space? Given a sorted list of integers where more than 50% of the list is the same integer, write a function to return the median value in O(1) computational time and space. Example input: li = [1, 2, 2]. Example output: median(li) -> 2.

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in "messy" datasets. Refer to the provided image of the datasets.

• How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice, and how would you assess its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which random forest generates its ensemble of trees. Additionally, discuss why one might choose random forest over logistic regression for certain problems.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe scenarios where you would prefer a bagging algorithm over a boosting algorithm, and discuss the tradeoffs between the two.

• How would you justify using a neural network for a business problem and explain its predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier? You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to evaluate the model's accuracy and validity?

What is the average salary for a Data Engineer at Ncino, Inc.?

Q: What is the interview process at nCino, Inc. like?

The interview process at nCino, Inc. typically involves several stages, including an initial screening with a recruiter, followed by technical interviews that test your coding, data manipulation, and problem-solving skills. The final stages often include behavioral interviews to assess cultural fit and a practical assessment of your engineering abilities.

Q: What are some common interview questions for the Data Engineer position at nCino, Inc.?

Common interview questions for the Data Engineer role at nCino, Inc. include questions on SQL, data modeling, ETL processes, Python programming, and problem-solving scenarios related to data pipelines and systems. Be prepared to discuss your previous experiences and how you've handled data engineering challenges.

Q: What skills are required to work as a Data Engineer at nCino, Inc.?

To succeed as a Data Engineer at nCino, Inc., you'll need strong technical skills in SQL, Python, ETL processes, and data warehousing. Experience with cloud platforms, such as AWS, and knowledge of big data tools like Hadoop or Spark are also highly valued. Analytical thinking and problem-solving skills are essential.

Q: What is the company culture like at nCino, Inc.?

nCino, Inc. prides itself on an inclusive and collaborative company culture. The organization values innovation, teamwork, and a customer-centric approach. Employees are encouraged to bring creative solutions to the table and thrive in a dynamic, fast-paced environment.

Q: How can I prepare for an interview at nCino, Inc.?

To prepare for your interview at nCino, Inc., research the company thoroughly and understand its products and services. Be sure to practice common data engineering interview questions, especially those relating to SQL and Python. Platforms like Interview Query can provide you with realistic practice scenarios and help you hone your skills.

If you want more insights about the company, check out our main ncino-inc 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 Ncino Inc.'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 Ncino Inc. 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!