Fall 2026 - Data Engineering Internship

Medlaunch Concepts is building a transformative healthcare accreditation platform that revolutionizes how clients manage compliance and regulatory processes. The Data Engineering Internship offers hands-on experience in developing data pipelines and analytics for healthcare systems, with responsibilities including building AWS functions, developing ETL workflows, and ensuring data quality.

Responsibilities:

• Build AWS Lambda functions for processing APIs and healthcare data sources
• Develop ETL pipelines using Python and SQL for healthcare compliance data
• Implement data validation and quality checks for sensitive healthcare information
• Create automated data processing workflows for accreditation documents
• Work with MongoDB Atlas and S3
• Design and optimize SQL database schemas
• Implement S3-based data lake architecture with Bronze/Silver/Gold zones
• Build caching systems using Redis for performance optimization
• Use/Configure Athena for interactive analytics and querying
• Create data feeds for executive dashboards and KPI tracking
• Build healthcare-specific analytics and benchmarking data pipelines
• Support Batch processing systems for hospital quality metrics
• Collaborate with our ML team to integrate predictive models into data workflows
• Build healthcare-specific analytics and benchmarking data pipelines using Athena for database queries
• Implement HIPAA-compliant data processing and audit trail systems
• Build data governance and documentation standards
• Create automated monitoring and alerting for data quality issues

Requirements:

• 1-3+ years with Python and SQL: Data processing, scripting, and database querying
• 1-2 years AWS Experience: knowledge of Lambda, S3, or other cloud data services
• Database Knowledge: Experience with SQL databases and/or NoSQL (MongoDB preferred)
• ETL/Data Processing: Understanding of data pipeline concepts and batch processing
• Experience with data transformation and cleaning
• Understanding of data warehousing and lake concepts
• Basic knowledge of data quality and validation techniques
• Familiarity with version control (Git) and collaborative development
• Healthcare or regulated industry experience
• Experience with Spark, Delta Lake, or distributed computing
• Knowledge of data visualization and BI tools
• Understanding of ML pipeline integration
• HIPAA compliance knowledge