Stage/Traineeship Data Engineer & Cloud at Blackbirds

📍 Job Overview

Job Title: Stage/Traineeship Data Engineer & Cloud
Company: Blackbirds
Location: Rotterdam, South Holland, Netherlands
Job Type: Full-Time
Category: Data Engineer
Date Posted: 2025-07-28

🚀 Role Summary

As a Stage/Traineeship Data Engineer & Cloud at Blackbirds, you will have the opportunity to gain practical experience in building modern data platforms and cloud-native solutions. You will work on client projects or internal initiatives that align with your learning goals. This role is ideal for starters or ambitious students looking to apply their technical skills in a practical setting.

📝 Enhancement Note: This role offers a unique opportunity for students to gain hands-on experience in data engineering and cloud technologies while working on real-world projects or internal initiatives.

💻 Primary Responsibilities

Build data pipelines in Azure or AWS, ensuring efficient data flow and processing.
Research efficient storage and processing methods, such as DuckDB, Parquet, or Delta Lake, to optimize data management.
Collaborate on data demos or prototypes, contributing to the development of innovative data solutions.
Work on internal projects, such as creating observability dashboards or test data generators, to improve Blackbirds' internal processes and capabilities.

📝 Enhancement Note: The primary responsibilities of this role require a strong focus on analytical thinking, structured working, and independence. Candidates should be eager to learn and adapt to new technologies and challenges.

🎓 Skills & Qualifications

Education: Pursuing a HBO or WO degree in Data Science, Computer Science, AI, or a related beta field.

Experience: Some experience in data analysis or development through hobby or study projects.

Required Skills:

Proficiency in Python and SQL
Basic knowledge of cloud platforms (Azure, AWS, or GCP)
Analytical thinking and structured working
Self-motivated and eager to learn

Preferred Skills:

Familiarity with data pipelines and ETL processes
Experience with data visualization tools (e.g., Power BI, Tableau)
Knowledge of data warehousing and data lakes

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Include relevant data analysis or development projects from your studies or hobbies.
Highlight your problem-solving skills and ability to work with data.
Showcase your understanding of data pipelines, ETL processes, and data management.

Technical Documentation:

Document your approach to data analysis and development, including any challenges faced and how you overcame them.
Include any relevant code snippets or visualizations to demonstrate your technical skills.

💵 Compensation & Benefits

Salary Range: €450 - €450 per month

Benefits:

Gain practical experience in data engineering and cloud technologies.
Work on real-world projects or internal initiatives that align with your learning goals.
Collaborate with experienced professionals in the field.

Working Hours: Full-time position with standard working hours (40 hours per week).

📝 Enhancement Note: The salary range for this role is based on industry standards for entry-level data engineering positions in the Netherlands. The benefits of this role focus on providing valuable learning experiences and the opportunity to work on real-world projects.

🎯 Team & Company Context

🏢 Company Culture

Industry: Blackbirds operates in the technology industry, focusing on data engineering and cloud solutions. This role will provide you with valuable insights into the tech industry and help you build a strong foundation for your career.

Company Size: As a trainee, you will join a small team, allowing you to have a significant impact on projects and contribute to the company's growth.

Founded: Blackbirds was founded with a mission to empower businesses with modern data platforms and cloud-native solutions. The company values innovation, collaboration, and continuous learning.

Team Structure:

Small, agile team with a flat hierarchy.
Collaborative environment with regular team meetings and knowledge-sharing sessions.
Close collaboration with clients on various projects.

Development Methodology:

Agile development processes with regular sprint planning and code reviews.
Focus on continuous integration, continuous deployment (CI/CD), and automated testing.
Emphasis on clean code, documentation, and knowledge sharing.

Company Website: Blackbirds Website

📝 Enhancement Note: Blackbirds' company culture emphasizes collaboration, innovation, and continuous learning. As a trainee, you will have the opportunity to work closely with experienced professionals and contribute to the company's growth.

📈 Career & Growth Analysis

Data Engineer Career Level: This role is an entry-level position focused on providing practical experience in data engineering and cloud technologies. You will work on real-world projects and gain valuable insights into the field.

Reporting Structure: As a trainee, you will report directly to the data engineering team lead or project manager. You will collaborate closely with the team and have regular check-ins to ensure your learning goals are being met.

Technical Impact: In this role, you will have the opportunity to contribute to the development of modern data platforms and cloud-native solutions. Your work will directly impact the company's ability to provide innovative data solutions to its clients.

Growth Opportunities:

Technical Skill Development: Gain practical experience in data engineering and cloud technologies, expanding your skill set and knowledge base.
Project Exposure: Work on real-world projects, allowing you to develop your problem-solving skills and gain experience in data management and processing.
Career Progression: Demonstrate your skills and commitment to the role, and you may have the opportunity to transition into a full-time position or take on more responsibilities within the team.

📝 Enhancement Note: This role offers significant growth opportunities for individuals looking to gain practical experience in data engineering and cloud technologies. By demonstrating your skills and commitment, you can position yourself for career progression within the company.

🌐 Work Environment

Office Type: Blackbirds operates a modern, collaborative workspace designed to foster innovation and creativity. The office is equipped with state-of-the-art technology and comfortable workspaces to support productive work.

Office Location(s): Rotterdam, Netherlands

Workspace Context:

Collaborative workspaces with ample room for team meetings and brainstorming sessions.
Access to modern technology and tools to support data engineering and cloud projects.
A supportive and inclusive work environment that values diversity and open communication.

Work Schedule: Full-time position with standard working hours (40 hours per week). Flexible working hours may be available to accommodate learning and development opportunities.

📝 Enhancement Note: Blackbirds' work environment is designed to support collaboration, innovation, and continuous learning. As a trainee, you will have access to modern technology and tools, as well as a supportive and inclusive work environment.

📄 Application & Technical Interview Process

Interview Process:

Online Assessment: Complete an online assessment to evaluate your technical skills and problem-solving abilities.
Technical Interview: Participate in a technical interview focused on your understanding of data engineering and cloud technologies. Be prepared to discuss your approach to data management, processing, and analysis.
Cultural Fit Interview: Engage in a cultural fit interview to assess your compatibility with Blackbirds' company culture and values.
Final Decision: The hiring team will make a final decision based on your technical skills, cultural fit, and alignment with the company's mission and values.

Portfolio Review Tips:

Highlight your relevant data analysis or development projects, demonstrating your problem-solving skills and ability to work with data.
Showcase your understanding of data pipelines, ETL processes, and data management.
Include any relevant code snippets or visualizations to demonstrate your technical skills.

Technical Challenge Preparation:

Brush up on your Python and SQL skills, as well as your understanding of cloud platforms (Azure, AWS, or GCP).
Familiarize yourself with data engineering concepts, such as data pipelines, ETL processes, and data warehousing.
Prepare for questions about your approach to data analysis and development, as well as your problem-solving skills and ability to work with data.

ATS Keywords: (Organized by category)

Programming Languages: Python, SQL
Cloud Platforms: Azure, AWS, GCP
Data Management: Data Pipelines, ETL, Data Warehousing, Data Lakes
Tools: (Relevant tools used in data engineering and cloud projects)
Soft Skills: Analytical Thinking, Structured Working, Independence, Eagerness to Learn

📝 Enhancement Note: The interview process for this role focuses on evaluating your technical skills, problem-solving abilities, and cultural fit. By preparing for the interview and showcasing your relevant projects and skills, you can increase your chances of success.

🛠 Technology Stack & Web Infrastructure

Cloud Platforms:

Azure
AWS
GCP

Data Management & Processing:

DuckDB
Parquet
Delta Lake
SQL (PostgreSQL, MySQL, etc.)
Python (Pandas, NumPy, etc.)

Tools & Frameworks:

(Relevant tools used in data engineering and cloud projects, such as data visualization tools, ETL tools, etc.)

📝 Enhancement Note: The technology stack for this role focuses on cloud platforms, data management, and processing. As a trainee, you will gain practical experience working with these technologies and tools.

👥 Team Culture & Values

Data Engineering Values:

Innovation: Continuously seek new and better ways to manage and process data.
Collaboration: Work closely with team members and clients to deliver high-quality data solutions.
Continuous Learning: Stay up-to-date with the latest trends and best practices in data engineering and cloud technologies.
Quality: Ensure the accuracy and reliability of data by implementing robust data management and processing practices.

Collaboration Style:

Agile and Adaptable: Work in an agile and collaborative environment, adapting to changing project requirements and priorities.
Open Communication: Foster open and transparent communication with team members and clients to ensure everyone is aligned and working towards the same goals.
Knowledge Sharing: Share your knowledge and expertise with team members to help them grow and develop their skills.

📝 Enhancement Note: Blackbirds' team culture values innovation, collaboration, and continuous learning. As a trainee, you will have the opportunity to work closely with experienced professionals and contribute to the company's growth.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Pipeline Optimization: Develop efficient data pipelines that minimize data loss and maximize performance.
Data Processing Scalability: Ensure that data processing solutions can scale to meet the demands of growing datasets and user bases.
Data Quality Assurance: Implement robust data quality assurance processes to ensure the accuracy and reliability of data.
Emerging Technologies: Stay up-to-date with the latest trends and best practices in data engineering and cloud technologies, and be prepared to adapt to new tools and platforms as they emerge.

Learning & Development Opportunities:

On-the-Job Training: Gain practical experience working on real-world projects and internal initiatives.
Mentorship: Work closely with experienced data engineers and cloud specialists to learn from their expertise and gain insights into best practices.
Conferences and Workshops: Attend industry conferences and workshops to stay up-to-date with the latest trends and best practices in data engineering and cloud technologies.

📝 Enhancement Note: This role offers significant technical challenges and growth opportunities for individuals looking to gain practical experience in data engineering and cloud technologies. By embracing these challenges and seeking out learning and development opportunities, you can expand your skill set and knowledge base.

💡 Interview Preparation

Technical Questions:

Data Pipeline Design: Explain your approach to designing efficient data pipelines that minimize data loss and maximize performance.
Data Processing Strategies: Discuss your strategies for processing large datasets and ensuring data quality and reliability.
Cloud Platforms: Demonstrate your understanding of cloud platforms (Azure, AWS, or GCP) and their features and benefits.
Data Management: Explain your approach to data management, including data warehousing, data lakes, and data governance.

Company & Culture Questions:

Company Mission: Explain why you are interested in working at Blackbirds and how your skills and experience align with the company's mission and values.
Team Dynamics: Describe your preferred working style and how you collaborate with team members to deliver high-quality data solutions.
Learning and Development: Discuss your approach to continuous learning and how you stay up-to-date with the latest trends and best practices in data engineering and cloud technologies.

Portfolio Presentation Strategy:

Project Walkthrough: Present your relevant data analysis or development projects, highlighting your problem-solving skills and ability to work with data.
Technical Deep Dive: Provide a detailed explanation of your approach to data management, processing, and analysis, including any challenges faced and how you overcame them.
Company-Specific Examples: Tailor your portfolio presentation to Blackbirds' company culture and values, demonstrating your understanding of the company's mission and how your skills and experience align with its goals.

📌 Application Steps

To apply for this Stage/Traineeship Data Engineer & Cloud position at Blackbirds:

Submit your application through the application link provided.
Customize your portfolio with live demos and responsive examples, highlighting your relevant data analysis or development projects.
Optimize your resume for data engineering roles, emphasizing your technical skills and project highlights.
Prepare for the technical interview by brushing up on your Python and SQL skills, as well as your understanding of cloud platforms (Azure, AWS, or GCP). Familiarize yourself with data engineering concepts and be prepared to discuss your approach to data analysis and development.
Research the company to gain a deeper understanding of Blackbirds' mission, values, and culture. Consider how your skills and experience align with the company's goals and objectives.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and data engineering industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Data Engineering-Specific Focus:

Tailor every section specifically to data engineering roles, emphasizing cloud platforms, data management, and processing.
Include data engineering methodologies, data pipeline design, and data warehousing principles.
Emphasize data quality assurance, data governance, and data-driven decision-making.
Address data engineering career progression paths and technical leadership opportunities in data teams.
Provide tactical advice for data portfolio development, live demonstrations, and project case studies.

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information.
Only include Enhancement Notes when making significant inferences about data engineering processes, cloud configuration, or team structure.
Be comprehensive but concise, prioritizing actionable information over descriptive text.
Strategically distribute data engineering and cloud-related keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and data engineering specialization.

Industry Expertise:

Include specific cloud platforms, data management tools, and infrastructure requirements relevant to the role.
Address data engineering career progression paths and technical leadership opportunities in data teams.
Provide tactical advice for data portfolio development, live demonstrations, and project case studies.
Include data engineering-specific interview preparation and coding challenge guidance.
Emphasize data pipeline design, data processing optimization, and data governance principles.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use data engineering and cloud industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to data engineering professionals.
Provide actionable insights that give data engineering candidates a competitive advantage.
Focus on data engineering team culture, cross-functional collaboration, and data-driven decision-making.

Technical Focus & Portfolio Emphasis:

Emphasize data pipeline design, data processing optimization, and data governance principles.
Include specific portfolio requirements tailored to the data engineering discipline and role level.
Address data quality assurance, data governance, and data-driven decision-making.
Focus on problem-solving methods, data processing optimization, and scalable data architecture.
Include technical presentation skills and stakeholder communication for data projects.

Avoid:

Generic business jargon not relevant to data engineering roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific data engineering role.
Marketing language unrelated to data engineering, cloud technologies, or data-driven decision-making.

Generate comprehensive, data engineering-focused content that serves as a valuable resource for data engineering professionals evaluating career opportunities and preparing for technical interviews in the data engineering industry.

Stage/Traineeship Data Engineer & Cloud