At a Glance
- Tasks: Design and maintain data pipelines, clean and validate datasets, and collaborate with a dynamic team.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Gain hands-on experience, mentorship, and a certificate upon completion.
- Other info: Flexible hours with opportunities for growth and learning in a supportive environment.
- Why this job: Work remotely on real-world projects and enhance your data engineering skills.
- Qualifications: Pursuing or completed a degree in relevant fields; basic SQL and Python knowledge required.
The predicted salary is between 20000 - 30000 £ per year.
We are seeking a motivated and detail-oriented Data Engineering Intern to join our client's growing data team. This internship offers an excellent opportunity to work on real-world data engineering projects, gain hands-on experience with modern data technologies, and contribute to building scalable data pipelines and analytics solutions. The ideal candidate should have a strong interest in data processing, databases, cloud technologies, and data-driven decision-making.
Key Responsibilities
- Assist in designing, developing, and maintaining ETL/ELT data pipelines.
- Collect, clean, transform, and validate large datasets from multiple sources.
- Support the development and optimization of data warehouses and data lakes.
- Work with structured and unstructured data to ensure quality and consistency.
- Monitor data workflows and troubleshoot pipeline failures.
- Assist in integrating APIs and third-party data sources.
- Collaborate with data analysts, software engineers, and business stakeholders.
- Document data processes, workflows, and technical specifications.
- Support data governance, security, and compliance initiatives.
- Participate in code reviews and contribute to process improvements.
Required Skills
- Pursuing or recently completed a degree in Computer Science, Information Technology, Data Science, Software Engineering, or a related field.
- Basic understanding of SQL and relational databases.
- Knowledge of Python for data processing and automation.
- Familiarity with data structures and algorithms.
- Understanding of ETL concepts and data modeling principles.
- Knowledge of Git/GitHub version control.
- Strong analytical and problem-solving skills.
- Good communication and teamwork abilities.
Preferred Skills
- Experience with Python libraries such as Pandas, NumPy, or PySpark.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Exposure to data warehousing solutions like Snowflake, BigQuery, or Redshift.
- Understanding of Apache Airflow, Kafka, Spark, or Hadoop.
- Knowledge of REST APIs and JSON data formats.
- Basic understanding of data visualization tools such as Power BI or Tableau.
What You'll Gain
- Hands-on experience working with an international client.
- Exposure to modern data engineering tools and technologies.
- Opportunity to work on real-world business datasets.
- Mentorship from experienced engineering professionals.
- Experience in cloud-based data infrastructure.
- Internship completion certificate and performance-based recommendation opportunities.
Selection Process
- Application Screening
- Technical Assessment (SQL/Python)
- Technical Interview
- Client Discussion (if required)
- Offer Release
Technical Skills Keywords
- SQL
- Python
- ETL
- ELT
- Data Engineering
- Data Pipelines
- Data Warehousing
- AWS
- Azure
- GCP
- Snowflake
- Spark
- Airflow
- Kafka
- Git
- APIs
- Data Modeling
- Big Data
- Analytics
- Cloud Computing
Employment Type: Internship
Work Mode: Fully Remote
Client Region: Australia
Experience Required: Freshers / Final-Year Students / Recent Graduates Welcome.
Data Engineering Intern employer: Stealth Startup
Stealth Startup is an exceptional employer that fosters a dynamic and inclusive remote work culture, perfect for aspiring data scientists. With a focus on professional growth, interns will gain invaluable hands-on experience while collaborating with experienced teams, all within the supportive framework of UK time zones. This role not only offers the chance to develop technical skills in Python and machine learning but also encourages innovation and creativity in solving real-world data challenges.
