Data Engineering Internship Programs
Build the data infrastructure of tomorrow with our intensive 12-week internship. Master data pipelines, cloud platforms, and distributed systems while working on real-world engineering challenges under expert mentorship.
Why Choose Our Data Engineering Internship
Proven results from our comprehensive training programs
Become a Data Engineer
Our Data Engineering Internship is designed to transform you from a beginner into a job-ready data engineer. You'll build production-grade data pipelines, work with cloud platforms, and learn the architectural principles behind scalable data systems.
Infrastructure Design
Learn to design and implement robust data architectures that can handle real-world scale and complexity using modern tools and cloud platforms.
Pipeline Development
Master ETL/ELT processes, workflow orchestration, and data pipeline construction with Airflow, Spark, and other industry-standard tools.
Cloud Platforms
Get hands-on experience with Azure data services including data lakes, warehouses, and streaming platforms.
Why Choose Our Internship
We prepare you for the realities of modern data engineering roles.
Production Projects
Build and deploy real data pipelines that process millions of records, not just classroom exercises. Your GitHub will showcase actual engineering work.
Cloud Certifications
Earn preparation for AWS Certified Data Analytics or Google Cloud Professional Data Engineer certifications with our specialized training modules.
Engineering Culture
Experience agile development, code reviews, CI/CD pipelines, and other professional engineering practices used in top tech companies.
Distributed Systems
Work with Spark, Kafka, and other distributed computing frameworks to process large datasets across clusters of machines.
Data Governance
Learn data quality monitoring, metadata management, and compliance requirements for production data systems.
Career Support
Get resume reviews, technical interview prep, and connections to our hiring partners in the data engineering space.
Internship Curriculum
Our comprehensive curriculum covers the essential skills every data engineer needs.
Database Fundamentals
Master relational databases (PostgreSQL), NoSQL systems (MongoDB), and data modeling. Learn optimization, indexing, and partitioning strategies for performance.
Data Pipelines
Build batch and streaming pipelines with Python, Airflow, and Kafka. Implement error handling, monitoring, and alerting for production systems.
Cloud Data Platforms
Work with AWS (Redshift, Glue, Kinesis), GCP (BigQuery, Dataflow), and Azure (Synapse, Data Factory) to build scalable data solutions.
Big Data Processing
Use Spark (PySpark) for distributed data processing. Learn partitioning strategies, optimization techniques, and cluster resource management.
Data Infrastructure
Design data lakes, warehouses, and lakehouses. Implement data quality checks, metadata management, and access control patterns.
Capstone Project
Design and implement an end-to-end data platform for a real business case, from ingestion to consumption layer, with documentation and deployment.
Internship Timeline
Our 12-week program is structured to build your skills progressively.
Weeks 1-2: Foundations
Setup development environment, learn core concepts of data engineering, and practice with SQL and Python for data processing.
Weeks 3-4: Databases & Pipelines
Work with relational and NoSQL databases. Build your first ETL pipelines with Python and implement basic scheduling.
Weeks 5-6: Workflow Orchestration
Master Airflow for pipeline orchestration. Learn DAG creation, task dependencies, and error handling patterns.
Weeks 7-8: Cloud Platforms
Deploy pipelines on AWS, GCP, and Azure. Work with managed services for data warehousing, ETL, and streaming.
Weeks 9-10: Distributed Systems
Process large datasets with Spark. Implement streaming solutions with Kafka. Learn optimization and monitoring techniques.
Weeks 11-12: Capstone & Deployment
Complete your end-to-end data platform project. Implement CI/CD, documentation, and present your solution to engineering leaders.
Internship Criteria
We're looking for candidates with these qualifications.
Education
- CS, Engineering, or related technical degree
- Strong foundation in algorithms and data structures
- Understanding of database concepts
- Minimum 3.2 GPA (or equivalent) preferred
Technical Skills
- Proficiency in at least one programming language
- Basic SQL knowledge
- Familiarity with command line
- Understanding of software development concepts
Personal Qualities
- Strong problem-solving skills
- Attention to system design
- Ability to work with ambiguity
- Passion for building robust systems
- Collaborative mindset
Program Options
Choose the option that best fits your needs and career goals.
Standard Internship
- 12-week structured program
- 4 engineering projects
- Weekly code reviews
- Group workshops
- Cloud platform credits
- Resume & GitHub profile review
Premium Internship
- All Standard features plus:
- Weekly 1:1 engineering mentorship
- Resume & GitHub profile review
- Technical interview coaching
- Extended cloud platform access
- Priority job referrals
- Alumni network access
Corporate Sponsored
- Need-based scholarships available
- Commitment to work with partner
- Same curriculum as Premium
- Additional cloud credits
- Potential job offer upon completion
- 1-year work commitment required
Intern Success Stories
Hear from our alumni about their internship experiences and career outcomes.
The capstone project I built during the internship became the centerpiece of my interviews. I was able to speak in depth about architectural decisions and tradeoffs, which impressed hiring managers. I accepted a Data Engineer role at a Fortune 500 company.
Coming from a software engineering background, I wanted to transition into data. The internship gave me the specialized skills I needed while letting me leverage my existing coding experience. I'm now building streaming pipelines at a major tech company.
The cloud platform experience was invaluable. Working with AWS and GCP services in realistic scenarios gave me confidence in interviews. I received multiple offers and chose a role with 40% higher compensation than my previous position.
Frequently Asked Questions
Find answers to common questions about our Data Engineering Internship.
No cloud experience is required. We start with fundamental concepts and provide guided tutorials for each platform. By the end, you'll have deployed multiple projects across AWS, GCP, and Azure. Many interns come in with no cloud experience but leave comfortable working with multiple platforms.
We recommend a computer with at least 16GB RAM (32GB ideal for local Spark work), a multi-core processor, and 50GB+ free storage. Most heavy processing will happen in the cloud, but local development benefits from these specs. Linux or MacOS is preferred but Windows with WSL works too.
This is a highly technical program focused on software engineering for data systems. You'll write substantial Python code, SQL queries, configuration files, and infrastructure-as-code. Comfort with programming concepts is essential, though we help you level up your skills throughout the program.
Plan for 20-25 hours per week: 6-8 hours of live sessions (evenings/weekends), 8-10 hours on projects, and 6-7 hours of self-paced learning. The program is intensive but structured to help you make consistent progress while balancing other commitments.
Yes! Our career team provides resume reviews, technical interview prep, and connections to hiring partners. Premium interns get priority referrals. While we can't guarantee employment, our 96% placement rate demonstrates our program's effectiveness in preparing candidates for data engineering roles.
Ready to Launch Your Data Engineering Career?
Applications for our next cohort are now open. Transform your career in 12 weeks with hands-on data engineering experience.