Data Engineering Intern
Location: Australia – Remote
Employment Type: Internship
Experience Level: Entry Level
Work Arrangement: Remote
About the Opportunity
We are hiring a Data Engineering Intern on behalf of one of our clients. This opportunity is designed for students, recent graduates, and aspiring Data Engineers who want to develop their technical skills and gain practical exposure to real-world data engineering projects.
The selected candidate will work alongside experienced professionals and gain exposure to data collection, data processing, database management, ETL/ELT pipelines, data integration, cloud technologies, and building reliable data infrastructure.
Key Responsibilities
- Assist in collecting, extracting, transforming, and loading data from various sources.
- Develop and maintain ETL/ELT data pipelines for structured and unstructured data.
- Clean, transform, validate, and organize datasets for analytical and business use.
- Work with relational and non-relational databases.
- Write SQL queries to retrieve, manipulate, join, and analyze data.
- Assist in designing and optimizing database tables, schemas, and data models.
- Support data integration from APIs, databases, files, and other sources.
- Monitor data pipelines and identify data quality or processing issues.
- Perform data validation and implement data quality checks.
- Assist with automation of repetitive data processing tasks.
- Work with batch and, where required, real-time data processing workflows.
- Collaborate with Data Scientists, Data Analysts, Software Engineers, and other technical teams.
- Document data pipelines, processes, workflows, and technical requirements.
- Assist with troubleshooting and improving data pipeline performance.
- Work with cloud-based data platforms and storage solutions as required.
- Stay informed about developments in Data Engineering, Cloud Computing, Big Data, and Artificial Intelligence.
Technical Skills
Candidates should have familiarity with some of the following:
- Python
- SQL
- Pandas
- NumPy
- ETL/ELT
- Data Pipelines
- Relational Databases
- Database Management
- Data Modeling
- Git/GitHub
- APIs
- Data Warehousing
- Data Processing
- Data Integration
Knowledge of Apache Spark, Airflow, AWS, Microsoft Azure, Google Cloud, Snowflake, Databricks, Docker, or Kafka will be considered an advantage.
Qualifications
- Currently pursuing or recently completed a degree in Computer Science, Data Engineering, Information Technology, Software Engineering, Mathematics, or a related discipline.
- Understanding of fundamental data engineering and database concepts.
- Basic to intermediate proficiency in Python.
- Familiarity with SQL and relational databases.
- Understanding of data structures, data processing, and data management.
- Basic understanding of ETL/ELT processes and data pipelines.
- Strong analytical and problem-solving abilities.
- Ability to work independently in a remote environment.
- Good written and verbal communication skills.
- Strong attention to detail and willingness to learn.
- Ability to manage tasks, meet deadlines, and collaborate effectively with a remote team.
Preferred Qualifications
- Academic or personal projects involving Data Engineering or Data Management.
- Experience working with databases or real-world datasets.
- Familiarity with cloud platforms.
- Knowledge of data warehousing and data modeling.
- Exposure to Apache Spark, Airflow, Kafka, or Databricks.
- Familiarity with Git and GitHub.
- Experience working with APIs or data integration tools.
- A portfolio, GitHub repository, or project demonstrating practical technical skills is an advantage.
Key Competencies
- Analytical Thinking
- Problem Solving
- Technical Thinking
- Attention to Detail
- Data Management
- Communication Skills
- Team Collaboration
- Time Management
- Adaptability
- Continuous Learning
What You Will Gain
- Practical exposure to real-world Data Engineering projects.
- Hands-on experience with data pipelines and data processing.
- Experience working with databases and SQL.
- Understanding of ETL/ELT workflows and data integration.
- Exposure to cloud-based data technologies.
- Experience collaborating with technical and data teams.
- Development of technical, analytical, and problem-solving skills.
- Practical understanding of modern data engineering workflows.
- Opportunity to strengthen your professional portfolio through project-based work.
Who Should Apply?
This opportunity is ideal for students, recent graduates, career starters, and aspiring Data Engineers who are interested in working with data infrastructure, databases, pipelines, cloud technologies, and data platforms.
Candidates who are analytical, technically curious, self-motivated, and eager to learn are encouraged to apply.
