Stealth Startup
Data Engineering Intern
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Data Engineering Internship – Remote | United Kingdom
We are hiring on behalf of one of our clients for a motivated and technically driven Data Engineering Intern to join their team remotely in the United Kingdom. This opportunity is suitable for candidates who are looking to gain practical experience in data engineering, data pipelines, databases, cloud technologies, and modern data infrastructure.
The selected candidate will have the opportunity to work on practical data-related projects, support data pipeline development, work with structured and unstructured datasets, and gain exposure to the technologies and processes used by modern data engineering teams.
Position Details
- Job Title: Data Engineering Intern
- Location: Remote – United Kingdom
- Employment Type: Internship
- Working Arrangement: Fully Remote
Key Responsibilities
- Assist in designing, developing, and maintaining data pipelines and ETL/ELT workflows.
- Collect, extract, transform, and load data from multiple sources.
- Work with structured and unstructured datasets to support business and analytical requirements.
- Assist in data cleaning, transformation, validation, and quality checks.
- Develop and optimise SQL queries for data extraction and processing.
- Work with relational and non-relational databases as required.
- Support the development and maintenance of data warehouses and data lakes.
- Assist in building automated data workflows and scheduled data processes.
- Monitor data pipelines and troubleshoot data processing issues.
- Collaborate with Data Scientists, Data Analysts, Software Engineers, and other stakeholders.
- Assist in implementing data quality, consistency, and reliability checks.
- Document data pipelines, workflows, processes, and technical solutions.
- Participate in technical discussions, project meetings, and code reviews.
- Research and learn new tools, frameworks, and technologies relevant to modern data engineering.
- Follow best practices for data security, governance, scalability, and maintainability.
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Required Skills and Qualifications
- Basic understanding of Data Engineering and data processing concepts.
- Good knowledge of SQL and relational databases.
- Familiarity with Python or another programming language used for data processing.
- Understanding of ETL/ELT concepts and data pipeline architecture.
- Basic knowledge of databases such as MySQL, PostgreSQL, SQL Server, or similar technologies.
- Familiarity with Git/GitHub and version-control concepts.
- Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud is an advantage.
- Knowledge of tools such as Apache Spark, Airflow, Kafka, or similar technologies is beneficial.
- Understanding of data warehousing and data modelling concepts is preferred.
- Strong analytical and problem-solving abilities.
- Good attention to detail and ability to work with large datasets.
- Strong communication and teamwork skills.
- Ability to work independently in a remote environment.
- Willingness to learn new technologies and adapt to evolving technical requirements.
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Who Can Apply?
This opportunity is suitable for:
- Students pursuing Data Engineering, Computer Science, Information Technology, Software Engineering, Data Science, or related disciplines.
- Recent graduates looking to gain practical industry experience.
- Candidates looking to transition into a career in Data Engineering.
- Individuals with relevant academic, personal, or portfolio projects.
- Candidates who have completed relevant courses or certifications in Python, SQL, databases, cloud computing, or data engineering.
- Candidates with a strong interest in building scalable data systems and working with modern data technologies.
What You Will Gain
- Hands-on exposure to real-world Data Engineering projects.
- Practical experience in data extraction, transformation, processing, and pipeline development.
- Exposure to databases, data warehouses, data lakes, and cloud-based data environments.
- Opportunity to strengthen your SQL, Python, and data engineering skills.
- Experience working with modern data engineering tools and technologies.
- Exposure to professional development workflows, Git, documentation, testing, and collaboration.
- Opportunity to build practical projects and strengthen your technical portfolio.
- Professional experience within a remote UK-based client environment.
- Better understanding of how data infrastructure supports analytics, AI, machine learning, and business operations.
- Valuable industry exposure to support future Data Engineering and related full-time career opportunities.
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