Jobs
Required Skills
SQL
Python
Tableau
PowerBI
Work Where You Matter:
At Dollar General, our mission is Serving Others! We value each and every one of our employees. Whether you are looking to launch a new career in one of our many convenient Store locations, Distribution Centers, Store Support Center or with our Private Fleet Team, we are proud to provide a wide range of career opportunities. We are not just a retail company; we are a company that values the unique strengths and perspectives that each individual brings. Your difference truly makes a difference at Dollar General. How would you like to Serve? Join the Dollar General Journey and see how your career can thrive.
Company Overview:
General Summary:
This role within Decision Science & Analytics will support the execution of the Company’s customer and marketing analytics program. This role will work collaboratively with the DG Marketing teams (both owned and paid media), third parties, and the broader decision science organization. Day to day work will included providing analysis to help curate audiences for campaign exposures, perform post-campaign analysis, and conduct various basket analytics. Projects may include automating analytics processes, creating/updating customer segmentations, or ad hoc open-ended deep dives into category performance.
Job Details
Duties & Responsibilities:
- Work cross functionally across the Marketing department understand their root business problem or question and how they could leverage data/insights.
- Translate data/insights needs into analytics techniques to produce data-driven and actionable insights.
- Present findings in PowerPoint or Tableau/PowerBI to stakeholders, “telling the story”With data to non-technical audiences.
- Create automated, reusable analytics workflows from end-to-end: from developing and maintaining SQL/Python code to the final report or dashboard deliverable.
- Answer ad-hoc Marketing/Vendors questions as needed with the ability to explain analytics or retail concepts.
- Balance a combination of quick turn reporting asks with deeper dive analysis and prioritize appropriately to meet deadlines.
Knowledge, Skills and Abilities (KSAs):
- Intermediate to Advanced SQL Skills.
- Intermediate Python skills.
- Intermediate skills with BI tools such as Tableau or PowerBI.
- Experience presenting insights to non-technical audience.
- Experience gathering user requirements for analysis or BI dashboards.
- Experience working with large datasets (millions of records).
- High-level written and verbal communication skills, including data design and BI best practices.
- Experience with retail industry or marketing and media networks is preferred.
- Experience with analytics platforms such as Databricks is preferred.
- Experience with code management tools such as Github is preferred.
Qualifications:
Work Experience &/or Education:
- Bachelor's degree from an accredited college or university in Data Analytics, Data Science, Business, Statistics, or Finance. Any suitable combination of education and experience will be considered.
- 2+ years of experience. Academic/Research experience in working with data science and analytics will be considered.
Duties & Responsibilities:
- Work cross functionally across the Marketing department understand their root business problem or question and how they could leverage data/insights.
- Translate data/insights needs into analytics techniques to produce data-driven and actionable insights.
- Present findings in PowerPoint or Tableau/PowerBI to stakeholders, “telling the story”With data to non-technical audiences.
- Create automated, reusable analytics workflows from end-to-end: from developing and maintaining SQL/Python code to the final report or dashboard deliverable.
- Answer ad-hoc Marketing/Vendors questions as needed with the ability to explain analytics or retail concepts.
- Balance a combination of quick turn reporting asks with deeper dive analysis and prioritize appropriately to meet deadlines.
Knowledge, Skills and Abilities (KSAs):
- Intermediate to Advanced SQL Skills.
- Intermediate Python skills.
- Intermediate skills with BI tools such as Tableau or PowerBI.
- Experience presenting insights to non-technical audience.
- Experience gathering user requirements for analysis or BI dashboards.
- Experience working with large datasets (millions of records).
- High-level written and verbal communication skills, including data design and BI best practices.
- Experience with retail industry or marketing and media networks is preferred.
- Experience with analytics platforms such as Databricks is preferred.
- Experience with code management tools such as Github is preferred.
Work Experience &/or Education:
- Bachelor's degree from an accredited college or university in Data Analytics, Data Science, Business, Statistics, or Finance. Any suitable combination of education and experience will be considered.
- 2+ years of experience. Academic/Research experience in working with data science and analytics will be considered.
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About Dollar General

Dollar General
PublicDollar General is a discount retail chain operating over 19,000 stores across the United States. The company offers everyday essentials including food, household items, health and beauty products, and seasonal merchandise at discounted prices.
10,001+
Employees
Goodlettsville
Headquarters
Reviews
2.9
6 reviews
Work Life Balance
1.5
Compensation
2.0
Culture
1.2
Career
2.5
Management
1.8
15%
Recommend to a Friend
Pros
Advancement to management positions possible
Can provide permanent employment after time
Open door policy mentioned
Cons
Toxic and miserable work environment
Mental health impacts including depression
Wage theft and break policy issues
Salary Ranges
55 data points
Mid/L4
Mid/L4 · Data Engineer
1 reports
$133,470
total / year
Base
$102,669
Stock
-
Bonus
-
$133,470
$133,470
Interview Experience
3 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Experience
Positive 33%
Neutral 1%
Negative 66%
Interview Process
1
In-store Interview
2
Recruiter Interview
3
Regional Director Interview and Store Walk
4
HR and Operations Director Interview
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