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/