Data Engineering Intern Opportunity

Location:
Australia Work Mode: 100% Remote About the Opportunity We are hiring for a Data Engineering position on behalf of one of our clients based in Australia. This opportunity is ideal for individuals passionate about building scalable data solutions, designing data pipelines, managing databases, and developing efficient data infrastructure. The selected candidate will be responsible for designing, developing, implementing, and maintaining data pipelines and infrastructure that enable organizations to collect, process, store, and access large volumes of data efficiently. The role involves working with modern data engineering technologies, cloud platforms, databases, and ETL processes while collaborating with data analysts, data scientists, and software engineering teams to ensure reliable and accessible data systems.

Key Responsibilities
• Design, develop, and maintain scalable data pipelines to collect and process data from multiple sources.
• Build and manage ETL/ELT workflows to extract, transform, and load data into appropriate storage systems.
• Develop and optimize data processing solutions to handle structured, semi-structured, and unstructured datasets.
• Work with relational and non-relational databases to manage, store, and retrieve large volumes of data.
• Design and maintain data warehouses, data lakes, and other data storage architectures.
• Develop, test, and optimize SQL queries to improve database performance and data retrieval efficiency.
• Build automated data integration workflows to ensure seamless data movement across different systems.
• Work with cloud platforms such as AWS, Microsoft Azure, or Google Cloud to develop and manage data infrastructure.
• Implement data validation, quality checks, and monitoring processes to maintain data accuracy and consistency.
• Identify and troubleshoot issues related to data pipelines, data processing, and database performance.
• Collaborate with Data Analysts, Data Scientists, and other technical teams to understand data requirements.
• Optimize data workflows for improved performance, scalability, reliability, and cost efficiency.
• Implement data security, access controls, and governance practices to protect organizational data.




• Maintain documentation of data architecture, pipelines, workflows, and technical processes.
• Explore and implement modern data engineering technologies and best practices to improve existing infrastructure. Technical Skills Required
• SQL: Strong knowledge of SQL queries, joins, CTEs, subqueries, stored procedures, indexing, and query optimization.
• Python: Proficiency in Python programming for data processing, automation, and pipeline development.
• ETL / ELT: Understanding of data extraction, transformation, loading processes, and data integration workflows.
• Apache Spark: Knowledge of distributed data processing using Apache Spark or PySpark.
• Apache Airflow: Familiarity with workflow orchestration, scheduling, and pipeline automation.
• Database Management: Experience or knowledge of MySQL, PostgreSQL, Microsoft SQL Server, Oracle, or similar databases.
• Data Warehousing: Understanding of data warehouse architecture, dimensional modelling, star schema, and snowflake schema.
• Cloud Platforms: Knowledge of AWS, Microsoft Azure, or Google Cloud Platform and their data engineering services.
• Big Data Technologies: Familiarity with Hadoop, Spark, Kafka, or other distributed data processing technologies.
• Data Lakes: Understanding of data lake architecture, data storage formats, and data management practices.
• Version Control: Knowledge of Git, GitHub, or GitLab for source code management and collaboration.
• Data Modelling: Ability to design efficient data models and develop structured data architectures.
• Data Quality & Governance: Understanding of data validation, data integrity, data security, and governance practices.
• Docker / CI-CD: Familiarity with containerization, deployment workflows, and continuous integration tools will be an advantage. Required Qualifications
• Bachelor's or Master's degree in Computer Science,



Information Technology, Data Engineering, Software Engineering, Data Science, or a related discipline.
• Strong understanding of database concepts, data structures, and data management principles.
• Practical knowledge of SQL and Python programming.
• Understanding of ETL/ELT processes and data pipeline architecture.
• Familiarity with relational databases and data warehousing concepts.
• Understanding of data processing, data integration, and data transformation techniques.
• Knowledge of cloud computing fundamentals and data infrastructure.
• Ability to troubleshoot technical issues and optimize data workflows.
• Strong analytical thinking and problem-solving abilities.
• Good communication and collaboration skills.
• Ability to work independently and manage technical responsibilities in a remote working environment. Preferred Qualifications
• Previous experience in Data Engineering, Database Development, Data Integration, or a related technical role.
• Experience developing and maintaining automated data pipelines.
• Familiarity with Apache Spark, PySpark, Airflow, Kafka, or similar technologies.
• Experience working with cloud-based data engineering services.
• Understanding of data lakehouse architecture and modern data platforms.
• Knowledge of DevOps practices, CI/CD pipelines, and containerization.
• Experience handling large-scale datasets and distributed computing environments.
• Familiarity with Agile development methodologies. What You Will Get
• Opportunity to work with one of our client organizations based in Australia.
• 100% remote working chance.
• Exposure to real-world data engineering projects and modern data infrastructure.
• Opportunity to work with advanced data engineering tools, technologies, and cloud platforms.
• Practical exposure to building and maintaining scalable data pipelines.
• Opportunity to collaborate with experienced technical professionals and cross-functional teams.
• Professional development and opportunities to strengthen technical and engineering expertise.
• Opportunity to contribute to data architecture, infrastructure development, and large-scale data projects.

📌 Data Engineering Intern (Australia)
🏢 Leading
📍 Australia