Data Engineering Intern

Data Engineering Intern

Company: MedReveal

Location: Remote (United States)

Job Type: Internship | Part-Time

Compensation: Unpaid Internship

Duration: 3 Months

About MedReveal

MedReveal is a healthcare technology startup building AI-powered solutions to help healthcare providers optimize their insurance payer contracts.

Our platform processes large-scale healthcare price transparency data to help medical practices benchmark reimbursement rates, evaluate payer contracts, and identify opportunities for better contract negotiations.

We're building scalable data infrastructure and AI-powered tools to transform complex healthcare pricing data into actionable insights.

About the Role

We're looking for a motivated and detail-oriented Data Engineering Intern to join our technical team.

In this role, you'll gain hands-on experience working with large-scale datasets, building data pipelines, optimizing database performance, and solving real-world data engineering challenges.

You'll work closely with our founding and engineering teams to learn how data infrastructure is designed, developed, and maintained in a growing healthcare technology startup.

This is an opportunity to gain practical exposure to big data processing, cloud infrastructure, ETL pipelines, and database management.

Key Responsibilities

• Assist in developing and maintaining ETL (Extract, Transform, Load) pipelines for large-scale healthcare datasets.
• Work with structured and semi-structured data formats, including JSON, CSV, Parquet, and compressed files.
• Support data extraction, transformation, cleaning, and standardization processes.
• Write and optimize SQL queries for data retrieval, analysis, and processing.
• Assist in database design, indexing, and query performance optimization.
• Work with large healthcare datasets containing provider information, reimbursement rates, and billing codes.
• Support data validation, quality checks, and duplicate detection.
• Help develop Python scripts to automate data processing workflows.
• Gain exposure to cloud-based data storage and computing infrastructure.
• Collaborate with the engineering team to improve data pipeline scalability, reliability, and efficiency.
• Document data workflows, processing logic, and technical procedures.

Required Skills

• Python: Basic to intermediate proficiency in Python programming, including data manipulation and scripting.
• SQL: Understanding of SQL queries, joins, aggregations, and relational databases.
• Data Processing: Familiarity with Pandas or similar Python data-processing libraries.
• Database Fundamentals: Basic understanding of PostgreSQL, MySQL, or other relational databases.
• ETL Concepts: Understanding of data extraction, transformation, loading, and data pipelines.
• Data Formats: Familiarity with JSON, CSV, and other common data formats.
• Problem-Solving: Strong analytical and debugging skills.
• Git & Version Control: Basic knowledge of Git and GitHub.
• Communication: Ability to collaborate with technical team members and document work clearly.
• Willingness to Learn: Interest in large-scale data engineering, cloud computing, and healthcare technology.

Preferred Skills (Not Required)

• Experience with AWS services such as S3, EC2, or RDS.
• Familiarity with PostgreSQL query optimization and indexing.
• Experience working with large datasets using Pandas, Polars, PySpark, or DuckDB.
• Understanding of parallel processing and memory-efficient data processing.
• Familiarity with REST APIs and automated data ingestion.
• Basic knowledge of Docker, Linux, and command-line tools.
• Understanding of data modeling, data warehousing, and database normalization.
• Exposure to healthcare datasets, NPI, CPT/HCPCS codes, or healthcare price transparency data.

Qualifications

• Pursuing or recently completed a degree in Computer Science, Data Science, Information Technology, Software Engineering, or a related field.
• Strong interest in data engineering, backend systems, and cloud infrastructure.
• Ability to work independently and collaborate in a remote team environment.
• Detail-oriented with a willingness to tackle complex technical challenges.
• Previous internships or professional experience are not required.

What You'll Gain

• Hands-on experience with real-world healthcare data engineering challenges.
• Exposure to large-scale datasets and data processing workflows.
• Practical experience using Python, SQL, PostgreSQL, and AWS.
• Understanding of how production data pipelines are designed and optimized.
• Experience with data quality, performance optimization, and automation.
• Direct mentorship from startup founders and engineers.
• Exposure to healthcare price transparency and AI-powered analytics.
• Opportunities to contribute to supervised technical projects.
• Portfolio-worthy engineering experience and professional development.
• Potential consideration for future paid opportunities based on performance and company needs.

Compensation & Internship Details

This is an unpaid internship focused on technical learning, mentorship, and practical industry exposure.

The internship includes structured training, supervised engineering projects, technical feedback, and professional development opportunities.

How to Apply

Interested candidates can apply by submitting their resume and, if available, links to their GitHub profile or relevant technical projects.

Join MedReveal and gain hands-on experience building data infrastructure for the next generation of AI-powered healthcare contract optimization.