Job Description

About the Internship:

This 3-month hands-on training internship is an opportunity to learn real-world, practical skills in data engineering while working on real projects that impact the industry. While the internship is unpaid, it provides unparalleled experience, mentorship, and the chance to develop your portfolio for future career opportunities. You’ll work closely with our team to understand the fundamentals of data engineering, gain exposure to advanced tools and technologies, and build projects you can showcase.

What You’ll Learn:

• Data Pipeline Development: Build and manage scalable ETL (Extract, Transform, Load) pipelines for data processing.

• Data Warehousing: Learn to design and optimize data storage for high-performance analytics.

• Big Data Tools: Gain hands-on experience with industry-standard tools like Apache Spark, Hadoop, and more.

• Cloud Platforms: Work with cloud services like AWS, Google Cloud, or Azure for data storage and analytics.

• Data Integration: Learn how to integrate data from multiple sources and maintain data quality.

• SQL & Python Programming: Build expertise in writing efficient queries and leveraging Python for data manipulation.

• Real-World Problem Solving: Participate in solving real-world challenges by contributing to live projects.

• Version Control & Collaboration: Use Git and agile methodologies to work collaboratively with a team.

Key Responsibilities:

• Assist in building, testing, and deploying data pipelines and workflows.

• Support the design and implementation of data models for efficient querying.

• Clean, process, and transform raw data into meaningful formats for analysis.

• Collaborate with team members to identify and resolve data engineering challenges.

• Document processes, workflows, and learnings to contribute to team knowledge.

What We’re Looking For:

• Passion for Data Engineering: A strong interest in data systems, analytics, and solving complex problems.

• Technical Skills: Basic knowledge of SQL, Python, or any other programming language. Familiarity with data structures is a plus.

• Curiosity & Willingness to Learn: Open to new tools, technologies, and methodologies.

• Team Player: Excellent communication and collaboration skills.

• Education: Computer Science, Data Science, or a related field (students or recent graduates preferred).

What You’ll Gain:

• Practical, real-world experience working on live data engineering projects.

• Mentorship from experienced professionals with deep industry expertise.

• A portfolio of completed projects to showcase your skills.

• Networking opportunities and a letter of recommendation upon successful completion of the program.

• A stepping stone toward a career in data engineering, data science, or related fields.

How to Apply:

Submit your CV along with a brief statement on why you’re interested in data engineering and this internship opportunity. Highlight any relevant coursework, personal projects, or technical experience.

Deadline: Applications will be accepted on a rolling basis until the positions are filled.

This is your chance to get hands-on experience, work with real-world data, and kick-start your journey into the world of data engineering! Join us at RoyaltyBusayo and be part of a legacy that builds future tech leaders.

Qualifications

University Hiring Program Eligibility Requirements:

• University Enrollment: Must be currently enrolled in and returning to an accredited degree-seeking academic program for at least 1 1/2 years (Spring 2027 grad or later) in the Fall.
• Internship Work Period: Must be available to work full-time (approximately 40 hours per week) during a 10-12 week period starting May or June. Specific start dates are shared during the recruiting process.

Required Skills and Experience

• Strong foundational skills in data engineering, ETL, and familiarity with tools like Jenkins, dbt, and Airflow.
• Strong coding skills in Python, Scala, and/or Java, with an emphasis on clean, maintainable, and efficient code for data processing.
• Proficient in designing, implementing, and optimizing ETL/ELT pipelines using tools like Apache Airflow, dbt, and AWS Glue to support scalable data workflows.
• Basic knowledge of SQL and NoSQL databases (e.g., MySQL, Postgres, MongoDB) and time-series databases (e.g., Druid, Influx).
• Familiarity with AWS (EC2, S3, RDS, Lambda, EKS, Kenesis, Athena, Glue, DynamoDB, Redshift, IAM) and an interest in cloud infrastructure.
• Understanding of security protocols, including SAML, OAUTH, JWT Token, and SSO.
• Experience in orchestrating data workflows and ETL processes using AWS Data Pipeline or AWS Step Functions.
• Knowledge of interactive data preparation for cleaning and transforming data.
• Interest or experience in data analytics (dashboards, insights) and tools like Tableau is a plus.
• Experience with or an interest in CI/CD pipelines and build tools like Jenkins, CircleCI, or GitLab.
• Deep knowledge of Apache Spark and Kafka for batch and real-time data processing at scale.

Required Education and Training

• Currently pursuing a degree in Computer Science, Software/Computer Engineering, Information Technology, Data Science, or a related field.

Preferred Skills and Experience

• Basic knowledge of SQL and NoSQL databases (e.g., MySQL, Postgres, MongoDB) and time-series databases (e.g., Druid, Influx).
• Familiarity with AWS (EC2, S3, RDS, Lambda, EKS, Kenesis, Athena, Glue, DynamoDB, Redshift, IAM) and an interest in cloud infrastructure.
• Understanding of security protocols, including SAML, OAUTH, JWT Token, and SSO.
• Experience in orchestrating data workflows and ETL processes using AWS Data Pipeline or AWS Step Functions.
• Knowledge of interactive data preparation for cleaning and transforming data.
• Interest or experience in data analytics (dashboards, insights) and tools like Tableau is a plus.
• Experience with or an interest in CI/CD pipelines and build tools like Jenkins, CircleCI, or GitLab.
• Deep knowledge of Apache Spark and Kafka for batch and real-time data processing at scale.

Additional Information

All your information will be kept confidential according to EEO guidelines.