Data Engineering Intern

Data Engineering Intern – Australia (Remote) Location: Australia – Remote Employment Type: Internship About the Role We are seeking a motivated and technically curious Data Engineering Intern on behalf of one of our clients in Australia. The role offers an opportunity to gain practical exposure to modern data infrastructure and contribute to projects involving data ingestion, transformation, storage, and processing. The successful candidate will work alongside technical and analytical teams to understand data requirements, support engineering workflows, and contribute to building reliable and scalable data solutions. Key Responsibilities Assist in developing and maintaining reliable data ingestion workflows from databases, APIs, files, and other data sources.Support the design and implementation of scalable ETL and ELT processes for business and analytical applications.Write, test, and optimize SQL queries for data extraction, transformation, and validation.Develop Python-based scripts and utilities to automate routine data-processing tasks.Assist in structuring datasets for downstream analytics, reporting, and machine-learning use cases.Contribute to the development and maintenance of data warehouse and data lake environments.Perform data profiling and investigate inconsistencies, missing values, duplicates, and other data-quality issues.Support the implementation of data validation and monitoring processes across engineering workflows.Assist with integrating data from multiple systems while maintaining consistency and accuracy.Participate in troubleshooting pipeline failures and identifying potential performance bottlenecks.Maintain technical documentation covering data flows, schemas, transformation logic, and engineering procedures.Work with cross-functional teams to translate business requirements into practical data solutions.Follow established practices for version control, testing, documentation, and secure data handling.Participate in technical discussions, code reviews, and continuous improvement initiatives. Required Qualifications & Skills Pursuing or recently completed a degree, diploma, or relevant qualification in Computer Science, Data Engineering, Software Engineering, Information Technology, or a related discipline.Working knowledge of SQL and relational database concepts.Basic programming experience with Python or a comparable programming language.Understanding of data structures, data processing, and database fundamentals.Familiarity with ETL/ELT workflows and data transformation principles.Basic understanding of data warehousing and data modelling concepts.Strong logical reasoning and troubleshooting abilities.Good attention to detail when working with technical and data-intensive tasks.Ability to communicate technical information clearly and work effectively within a remote team.Strong willingness to learn and adapt to new technologies and engineering practices. Desirable Technical Exposure Candidates with exposure to any of the following will be considered favourably: AWS, Microsoft Azure, or Google Cloud PlatformApache Spark, Databricks, Apache Airflow, or KafkaSnowflake, BigQuery, Amazon Redshift, or other cloud data warehousesREST APIs and data integration techniquesGit/GitHub and collaborative development workflowsDocker or containerized development environmentsData lake and lakehouse architecturesBasic understanding of CI/CD practicesData modelling, schema design, and query optimization Learning & Professional Development During the internship, candidates may gain exposure to: Designing and maintaining production-oriented data workflows.Cloud-based data engineering architectures and services.Data ingestion, transformation, orchestration, and pipeline monitoring.Data warehouse and data lake implementation concepts.Engineering practices for data quality, reliability, and scalability.Collaborative development using version control and documentation standards.Solving practical data challenges within a professional technology environment.Working with cross-functional teams across data, technology, and business functions. Ideal Candidate We are looking for someone who demonstrates curiosity, technical aptitude, structured thinking, and a genuine interest in data infrastructure. The ideal candidate should be comfortable learning independently, asking thoughtful questions, investigating technical problems, and applying new concepts to practical projects.