Data Analytics Intern: AI & DataOps Training

Highmark Health Company; Pittsburgh (Allegheny County); On-site; USD 25,000 - 39,000; Part time

Job summary

enGen Summer 2027 Data Analyst Undergraduate Internship offers hands-on experience supporting data platforms, data operations, analytics, and AI-driven initiatives within enGen. Students will work with data engineers, analysts, and business stakeholders to learn DataOps practices and enterprise data management solutions.

You'll gain exposure to Atlan, Monte Carlo, Starburst, and dbt, develop SQL queries, participate in AI projects, and build skills across Data Analytics, Data Engineering, and

Qualifications

• Full or part-time enrollment in an accredited college or university baccalaureate program.
• Currently pursuing a degree in Information Science & Technology (IST), Computer Science, Management Information Systems (MIS), Data Analytics, Data Science, or a related technology discipline.
• Experience with SQL and writing database queries.
• Experience with or coursework in Python programming.

Responsibilities

• Analyze data and develop SQL-based queries and reporting solutions.
• Support data engineering and DataOps initiatives.
• Assist with data quality and observability efforts.
• Participate in AI-related projects and collaborate with cross-functional teams.
• Research technical solutions and support enterprise data platforms.

Skills

SQL

Python

Education

Full or part-time enrollment in an accredited college or university baccalaureate program

Tools

Atlan

Monte Carlo

Starburst

dbt

Job description

enGen Summer 2027 Data Analyst Undergraduate Internship offers hands-on experience supporting data platforms, data operations, analytics, and AI-driven initiatives within enGen. Students will work with data engineers, analysts, and business stakeholders to learn DataOps practices and enterprise data management solutions.

You'll gain exposure to Atlan, Monte Carlo, Starburst, and dbt, develop SQL queries, participate in AI projects, and build skills across Data Analytics, Data Engineering, and