Pay
$94.4K–$145K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,036 postings in the last year. Stated ranges, not salaries paid.
Data Analyst Intern (Summer 2027)
Greensboro, NC
Live, first seen by us 58 days ago- Pay
- Pay not listedSimilar roles state $94K–$145K
- Work setting
- Not stated
- Employment
Temporary — employment source
Employment type in the employer’s posting: TEMP
From the employer’s posting
Before you apply
- New graduates
- For current students
Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Information Systems, Mathematics, or a related field
What you’ll work on
Full postingWe are seeking a detail-oriented and technically minded Data Analyst Intern to join our team.
Compare source systems against the Data Warehouse to validate extracts and transforms
Run regression tests on data outputs after system or pipeline changes
Write SQL scripts to find nulls, duplicates and schema mismatches
Document data anomalies and track them to resolution with engineers
Research data sources to build supplier n-tier maps
From the employer’s posting
We are seeking a detail-oriented and technically minded Data Analyst Intern to join our team. In this role, you will work within our on-premise data environment, ensuring the accuracy and reliability of the data that powers our business decisions. A significant portion of this internship focuses on data quality assurance (QA). You will ensure that our data is accurate, consistent, and reliable by performing rigorous testing and validation.
Perform comparative analysis between source systems and our Data Warehouse
Validate data outputs after system updates or pipeline changes
Write SQL scripts to proactively identify nulls, duplicates, or schema mismatches
Document data anomalies clearly and track them to resolution
Research and identify data sources to build supplier n-tier maps
What you’ll bring
All qualificationsCore experience
- SQL (Essential): Strong proficiency in writing SQL queries.
- Communication: Ability to clearly report bugs and explain "why" a data point looks wrong to stakeholders.
Preferred experience
- Familiarity with kubectl is a plus.
Qualification wording
SQL (Essential): Strong proficiency in writing SQL queries. You must be able to write queries to test data (e.g., finding set differences, counting variances).
Communication: Ability to clearly report bugs and explain "why" a data point looks wrong to stakeholders.
Kubernetes: Basic conceptual understanding of containerization. Familiarity with kubectl is a plus.
Education & alternatives
Education - Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Information Systems, Mathematics, or a related field. Technical Skills & Knowledge
About Apexanalytix-Careers
At apexanalytix, we’re lifelong innovators!
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 16, 202658 days ago
- Recorded sightings
- 59
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 58
Up longer than most. Similar jobs usually come down between day 5 and day 43.
From 14,545 similar postings that came down. Coming down is not always a hire.
Apexanalytix-Careers is hiring
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Bash
- Python
- Shell
- SQL
- Kubernetes
- pandas
Where the posting names them
- SQL (Essential): Strong proficiency in writing SQL queries. You must be able to write queries to test data (e.g., finding set differences, counting variances). - Linux / Command Line: Comfort working in a Linux environment. You should know basic shell commands (bash) for file management and log inspection. - Kubernetes: Basic conceptual understanding of containerization. Familiarity with kubectl is a plus.
- Data Concepts: Understanding of Data Warehousing (Star Schema) and ETL processes. - Programming: Basic proficiency in Python (Pandas) for scripting or data automation. - QA Mindset: A natural skepticism of data. You should have the habit of asking, "Does this number actually make sense?"
- Regression Testing: Validate data outputs after system updates or pipeline changes to ensure existing reports and dashboards remain accurate. - Data Integrity Checks: Write SQL scripts to proactively identify nulls, duplicates, or schema mismatches before they impact the business. - Bug Reporting: Document data anomalies clearly and track them to resolution, working closely with engineers to identify the root cause.
Analysis & Technical Operations - Data Analysis: Write complex SQL queries to extract and manipulate data for ad-hoc business requests. - Infrastructure Interaction: Use the Linux command line to navigate servers, execute validation scripts, and grep logs for errors.
Technical Skills & Knowledge - SQL (Essential): Strong proficiency in writing SQL queries. You must be able to write queries to test data (e.g., finding set differences, counting variances). - Linux / Command Line: Comfort working in a Linux environment. You should know basic shell commands (bash) for file management and log inspection.
- Infrastructure Interaction: Use the Linux command line to navigate servers, execute validation scripts, and grep logs for errors. - Kubernetes Support: Assist in monitoring data applications running on Kubernetes; check pod status and retrieve logs (kubectl logs) to aid in debugging QA failures. - Documentation: Maintain the Data Catalog and Business Glossary, ensuring that metric definitions match the technical reality of the data.
- Linux / Command Line: Comfort working in a Linux environment. You should know basic shell commands (bash) for file management and log inspection. - Kubernetes: Basic conceptual understanding of containerization. Familiarity with kubectl is a plus. - Data Concepts: Understanding of Data Warehousing (Star Schema) and ETL processes.
Your next step
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Demand for Analyst roles
New Analyst postings at the employers we follow are up 23% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Analyst, by the work the posting describes.
Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.
Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.
Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.
Job description
About Us:
At apexanalytix, we’re lifelong innovators! Since the date of our founding nearly four decades ago we’ve been consistently growing, profitable, and delivering the best procure-to-pay solutions to the world. We’re the perfect balance of established company and start-up. You will find a unique home here.
And you’ll recognize the names of our clients. Most of them are on The Global 2000. They trust us to give them the latest in controls, audit and analytics software every day. Industry analysts consistently rank us as a top supplier management solution, and you’ll be helping build that reputation.
Read more about apexanalytix - https://www.apexanalytix.com/about/
Position Title: Data Analyst Intern
Reports to: Manager, Automation Architect
Location: Greensboro, N.C.
POSITION SUMMARY
We are seeking a detail-oriented and technically minded Data Analyst Intern to join our team. In this role, you will work within our on-premise data environment, ensuring the accuracy and reliability of the data that powers our business decisions. A significant portion of this internship focuses on data quality assurance (QA). You will ensure that our data is accurate, consistent, and reliable by performing rigorous testing and validation.
KEY RESPONSIBILITIES:
Data Quality Assurance (QA) & Testing
- Source-to-Target Validation: Perform comparative analysis between source systems and our Data Warehouse to ensure data was extracted and transformed correctly.
- Regression Testing: Validate data outputs after system updates or pipeline changes to ensure existing reports and dashboards remain accurate.
- Data Integrity Checks: Write SQL scripts to proactively identify nulls, duplicates, or schema mismatches before they impact the business.
- Bug Reporting: Document data anomalies clearly and track them to resolution, working closely with engineers to identify the root cause.
Analysis & Technical Operations
- Data Analysis: Write complex SQL queries to extract and manipulate data for ad-hoc business requests.
- Infrastructure Interaction: Use the Linux command line to navigate servers, execute validation scripts, and grep logs for errors.
- Kubernetes Support: Assist in monitoring data applications running on Kubernetes; check pod status and retrieve logs (kubectl logs) to aid in debugging QA failures.
- Documentation: Maintain the Data Catalog and Business Glossary, ensuring that metric definitions match the technical reality of the data.
- Supplier N-Tier Mapping: Research and identify data sources to build supplier n-tier maps, discovering relationships between Tier 1 suppliers and their upstream sub-suppliers (Tier 2, Tier 3, etc.).
POSITION REQUIREMENTS:
Education
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Information Systems, Mathematics, or a related field.
Technical Skills & Knowledge
- SQL (Essential): Strong proficiency in writing SQL queries. You must be able to write queries to test data (e.g., finding set differences, counting variances).
- Linux / Command Line: Comfort working in a Linux environment. You should know basic shell commands (bash) for file management and log inspection.
- Kubernetes: Basic conceptual understanding of containerization. Familiarity with kubectl is a plus.
- Data Concepts: Understanding of Data Warehousing (Star Schema) and ETL processes.
- Programming: Basic proficiency in Python (Pandas) for scripting or data automation.
- QA Mindset: A natural skepticism of data. You should have the habit of asking, "Does this number actually make sense?"
Soft Skills & Attributes
- Attention to Detail: The ability to spot small discrepancies in large datasets.
- Technical Curiosity: A desire to understand the infrastructure (servers/containers) that supports the data.
- Communication: Ability to clearly report bugs and explain "why" a data point looks wrong to stakeholders.
Over the years, we’ve discovered that the most effective and successful associates at apexanalytix are people who have a specific combination of values, skills, and behaviors that we call “The apex Way”. Read more about The apex Way - https://www.apexanalytix.com/careers/
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Greensboro, NC
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.