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- Tasks: Design, build, and maintain data pipelines while solving real-world data challenges.
- Company: Join a reputed IT company with a focus on innovative data solutions.
- Benefits: Enjoy 1:1 mentorship, internship certificate, and potential stipend based on your contributions.
- Why this job: Gain hands-on experience in data engineering and work on impactful projects.
- Qualifications: Basic SQL and Python knowledge; no fancy degree required, just a passion for data.
- Other info: Flexible remote work for 15-20 hours/week over 3 months.
Summer Internship – Data Engineering (Beginner to Intermediate Levels Welcome)
Duration: 3 Months | Remote | Flexible Start
Interested in building the backbone that powers modern data systems? Whether you’re just starting out or have some experience with data pipelines — this internship gives you real-world exposure to how data is collected, processed, and delivered at scale.
HIRIST is hiring Data Engineering Interns for a reputed IT client, where you’ll work alongside data engineers solving practical data infrastructure challenges.
What You’ll Work On:- Assist in designing, building, and maintaining data pipelines
- Work with structured and unstructured datasets from real business systems
- Support ETL/ELT processes using SQL, Python, or cloud-based tools
- Learn how to optimize data workflows for reliability and performance
- Help maintain data quality, governance, and documentation standards
- Students or recent grads from computer science, engineering, or data backgrounds
- Learners who enjoy solving problems through data structure, pipelines, and systems
- Beginners with some hands-on experience in SQL, Python, or data handling
- Intermediate learners looking to gain practical skills in building data infrastructure
You don’t need a fancy degree — just the drive to learn, experiment, and build.
Must-Have Skills:- Basic understanding of SQL and Python
- Familiarity with databases (relational or NoSQL)
- Interest in data flow, storage, and processing
- Good logical thinking and attention to detail
- Experience with data pipeline tools like Apache Airflow, DBT, or Kafka
- Knowledge of cloud data services (AWS S3/Glue/Redshift, GCP BigQuery, Azure Data Factory)
- Exposure to Spark, Hadoop, or other big data frameworks
- Personal or academic data engineering projects
- 1:1 mentorship with senior data engineers
- Live experience with production-grade data infrastructure
- Internship Certificate upon completion
- Letter of Recommendation based on performance
- Stipend opportunity based on skill and contribution
- Resume Screening (look for data interest and logical mindset)
- Beginner-friendly Data Engineering Task or quiz
- Friendly Interview with Data Engineering Mentor/Manager
- Final Selection & Onboarding via HIRIST
- Are available for 4–12 weeks
- Can commit 15–20 hours/week remotely
- Want to work on real data engineering tasks (not training simulations)
- Are serious about launching your career in data infrastructure
Ready to Build the Data Backbone? Apply with your resume + any optional GitHub/project portfolio link.
HIRIST – Connecting future builders to real tech teams.
Internship: Data Engineering employer: Hirist
Contact Detail:
Hirist Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Internship: Data Engineering
✨Tip Number 1
Familiarise yourself with the tools and technologies mentioned in the job description. Even if you don't have extensive experience, showing that you've explored SQL, Python, or cloud services like AWS can set you apart.
✨Tip Number 2
Engage with online communities or forums related to data engineering. This will not only enhance your knowledge but also help you network with professionals who might provide insights or referrals for internships.
✨Tip Number 3
Prepare for the friendly interview by brushing up on your logical thinking skills. Practising problem-solving questions related to data structures and pipelines can give you a confidence boost.
✨Tip Number 4
If you have any personal or academic projects related to data engineering, be ready to discuss them. Highlighting your hands-on experience, even if it's minimal, shows your enthusiasm and commitment to learning.
We think you need these skills to ace Internship: Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights any relevant experience with SQL, Python, or data handling. Include any academic projects or personal initiatives related to data engineering to showcase your skills.
Craft a Compelling Cover Letter: Write a cover letter that expresses your enthusiasm for data engineering and outlines why you're a good fit for the internship. Mention specific skills you possess that align with the job description, such as your understanding of data pipelines or your logical thinking abilities.
Showcase Your Projects: If you have a GitHub or project portfolio, include it in your application. Highlight any relevant projects that demonstrate your ability to work with data, such as building data pipelines or using cloud services.
Prepare for the Interview: Research common data engineering concepts and be ready to discuss your understanding of SQL, Python, and data workflows. Think of examples from your experience that illustrate your problem-solving skills and attention to detail.
How to prepare for a job interview at Hirist
✨Show Your Passion for Data
Make sure to express your enthusiasm for data engineering during the interview. Talk about any personal projects or coursework that sparked your interest in data pipelines and processing. This will demonstrate your genuine interest in the field.
✨Brush Up on SQL and Python
Since a basic understanding of SQL and Python is essential, review key concepts and be prepared to discuss how you've used these languages in past projects or assignments. You might even be asked to solve a simple problem using them during the interview.
✨Prepare for Practical Questions
Expect questions that assess your logical thinking and problem-solving skills. Be ready to tackle scenarios related to data flow, storage, and processing. Practising with real-world examples can help you articulate your thought process effectively.
✨Ask Insightful Questions
At the end of the interview, take the opportunity to ask thoughtful questions about the team, the projects you'll be working on, and the tools they use. This shows your eagerness to learn and engage with the role, making a positive impression on your interviewers.
