Dollar General Corporation has been delivering value to shoppers for over 80 years, offering a wide range of everyday essentials at competitive prices across more than 18,000 stores in 47 states. Dollar General is on a mission to save time and money for its customers every day.

Stepping into a role as a Data Engineer at Dollar General means assembling and optimizing large data sets to meet business needs, automating processes, and building robust data infrastructure using SQL and cloud technologies. Expect to work with diverse teams to develop tools that provide actionable insights into key business performance metrics.

If you’re looking to join a company with a growing presence, this guide on Interview Query will walk you through the interview process, commonly asked questions, and offer valuable tips to help you succeed. Let’s get started!

Submitting Your Application

The first step to joining Dollar General as a Data Engineer is to submit a compelling application that highlights your technical skills and aligns with the company's values. Whether you were contacted by a Dollar General recruiter or are applying independently, it’s crucial to review the job description meticulously and tailor your CV accordingly.

Enhancing your CV may involve identifying specific keywords from the job listing and curating a targeted cover letter. Make sure to emphasize relevant skills and pertinent work experiences.

Recruiter/Hiring Manager Call Screening

If your CV gets shortlisted, a recruiter from Dollar General’s Talent Acquisition Team will reach out to confirm key details such as your experiences and skill levels. This initial screening might also involve behavioral questions.

Sometimes, the hiring manager for the Data Engineer role might participate in the screening round to answer your questions about the position and the company. They may also discuss surface-level technical and behavioral topics.

Typically, this call lasts around 30 minutes.

Technical Virtual Interview

After successfully passing the recruiter screening, you’ll receive an invitation for a technical screening round. The technical interview for the Data Engineer role at Dollar General usually takes place virtually, encompassing video conferencing and screen sharing. During this 1-hour long interview, expect questions revolving around Dollar General’s data systems, ETL pipelines, and SQL queries.

You may also receive take-home assignments related to data engineering, including tasks like building and optimizing data pipelines. Your expertise in areas such as SQL, cloud technologies, and programming languages (e.g., Python, Java) will likely be tested.

Depending on the position's seniority, you might also need to tackle case studies or practical problems.

Onsite Interview Rounds

Following a second recruiter call to outline the next steps, you’ll be invited to an onsite interview loop. Over the course of the day at the Dollar General office, several interview rounds will assess your technical skills, including programming and data infrastructure.

If you were given a take-home assignment, there may be a presentation round where you discuss your solution. Additionally, expect to discuss your approach to data engineering challenges, optimize workflows, and interact with various data-related issues.

Quick Tips For Dollar General Data Engineer Interviews

Brushing up on technical skills and practicing mock interviews can be highly beneficial. Here are a few tips to excel in your Dollar General interview:

• Master SQL and Data Pipelines: Ensure you have strong foundational knowledge and practical experience with SQL and data pipeline tools, as these are crucial to the Data Engineer role at Dollar General.
• Familiarize with Cloud Technologies: Experience with Snowflake, Azure cloud services, or similar platforms is often required. Understanding these technologies can boost your chances.
• Focus on Problem-Solving: Expect to solve case studies and real-world problems. Demonstrating your ability to optimize data processes and handle complex data sets will be advantageous.

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

• Create a function recurring_char to find the first recurring character in a string. Given a string, write a function recurring_char to find its first recurring character. Return None if there is no recurring character. Treat upper and lower case letters as distinct characters. Assume the input string includes no spaces.

• Write a query to get the average order value by gender. Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. Round your answer to two decimal places.

• Identify first-time and repeat purchases by product category. Analyze a user's purchases to identify which purchases represent the first time the user has bought a product from its category and which represent repeat purchases. Output a table including every purchase with a boolean column indicating if it’s a repeat purchase.

• Parse the most frequent words used in poems. Given a list of strings called sentences, return a dictionary of the frequency that words are used in the poem. Process all words as lowercase and ignore punctuation marks.

• 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, select the next highest salary.

• What would you do if friend requests are down 10% on Facebook? A product manager at Facebook informs you that friend requests have decreased by 10%. How would you approach diagnosing and addressing this issue?

• How would you set up an A/B test for changes in a sign-up funnel? 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 metrics would you use to determine the value of each marketing channel? Given all the different marketing channels and their respective costs at a company selling B2B analytics dashboards, what metrics would you use to evaluate the value of each channel?

• How would you measure the success of a banner ad strategy for an online media company? An online media company wants to experiment with adding web banners in the middle of its reading content to monetize effectively. How would you measure the success of this strategy?

• How would you investigate a drop in posts per user on Facebook? The posting tool on Facebook drops from 3% posts per user last month to 2.5% posts per user today. How would you investigate this issue? If the drop is in photo posts, what would you investigate next?

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• What is the difference between covariance and correlation? Provide an example. Describe the difference between covariance and correlation, and provide an example to illustrate the distinction.

• What are time series models? Why do we need them when we have less complicated regression models? Explain what time series models are and why they are necessary despite the availability of simpler regression models.

• How would you determine if the difference between this month and the previous month in a time series dataset is significant? Given a time series dataset grouped monthly for the past five years, describe how you would assess if the difference between this month and the previous month is significant.

• How would you address a manager's complaint about a packet filling machine not functioning correctly? A manager reports that a packet filling machine, which aims to place 25 packets into a box, is malfunctioning. Customers are complaining about incorrect packet counts. How would you investigate and resolve this issue?

• How does random forest generate the forest and why use it over logistic regression? Explain the process of generating a forest in random forest and discuss the advantages of using random forest over logistic regression.

• How would you justify using a neural network model and explain its predictions to non-technical stakeholders? Describe how you would justify the complexity of a neural network model for solving a business problem and how you would explain its predictions to non-technical stakeholders.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain the interpretation of logistic regression coefficients for categorical and boolean variables.

• Which model would perform better for predicting Airbnb booking prices: linear regression or random forest regression? Compare the performance of linear regression and random forest regression for predicting booking prices on Airbnb and explain which model would perform better and why.

• What are the assumptions of linear regression? List and explain the assumptions that must be met for linear regression to be valid.

What is the average salary for a Data Engineer at Dollar General?

Q: What is Dollar General's mission and vision? Dollar General aims to provide value to shoppers by offering essential products at everyday low prices in convenient locations. They strive for their customers to "Save time. Save money. Every day."

Q: What does a Data Engineer at Dollar General do? A Data Engineer at Dollar General works on assembling large, complex data sets, identifying and implementing process improvements, and building infrastructure for data extraction, transformation, and loading. They also develop analytics tools to deliver actionable insights and support the data-related needs of various teams.

Q: What skills are required for the Data Engineer position at Dollar General? Candidates need advanced SQL knowledge, experience with relational and NoSQL databases, and familiarity with programming languages like Python and Java. Proficiency in working with big data tools (Hadoop, Spark), cloud services (Snowflake, Azure), and data pipeline management tools (Azkaban, Luigi, Airflow) is also essential.

Q: What are the educational and experience requirements for this role? Applicants should have at least a BS in Computer Science or a related field, although a Master's degree is preferred. Additionally, 4+ years of experience in Python or Java development, SQL, schema design, and data modeling are required.

Q: How can I prepare for an interview at Dollar General for the Data Engineer role? Research the company and its mission, understand the job responsibilities, and brush up on your technical skills, especially in SQL, big data, and cloud technologies. Practice common interview questions and review your past projects to showcase your experience effectively.

To sum up, Dollar General is a powerhouse serving communities for over 80 years with 18,000+ stores and a commitment to delivering value. The Data Engineer position demands proficiency in SQL, cloud technologies, and an array of data tools, with a clear focus on innovation and efficiency. If you're enthusiastic about tackling complex data challenges and optimizing processes, this role presents a fantastic opportunity.

For more insights about the company, check out our main Dollar General Interview Guide, where we have covered numerous 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 Dollar General’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 Dollar General 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!