Data Engineer
Location: Netherlands / Hybrid / Remote
Job Type: Internship, Freelance, Parttime, Fulltime
Industry: Hospitality / Property Management / PropTech
Responsibilities: In consultation
What You’re Going to Do:
As a Data Engineer you are going to design reliable data pipelines, enable analytics at scale, and help turn platform and community interactions into meaningful insights.
You’ll design and operate the data infrastructure that powers product decisions, growth, and trust.
- Build scalable data pipelines and data models
- Ensure data quality, reliability, and accessibility
- Enable analytics, reporting, and experimentation
- Collaborate with Product, Engineering, Growth, and Finance
- Support data-driven decision making across the company
- Lay the groundwork for advanced analytics and ML
Your Key Responsibilities
- Design and maintain ETL/ELT pipelines
- Manage data warehouses and data lakes
- Model data for analytics, dashboards, and reporting
- Ensure data accuracy, consistency, and freshness
- Implement monitoring, testing, and documentation
- Optimize pipeline performance and costs
- Support privacy, security, and compliance requirements
Bonus If You Have Experience With
- Cloud data platforms (AWS, GCP, Azure)
- Data warehouses (Snowflake, BigQuery, Redshift)
- Orchestration tools (Airflow, Dagster, Prefect)
- Streaming technologies (Kafka, Kinesis, Pub/Sub)
- dbt and analytics engineering
- SQL at an advanced level
- Product analytics and experimentation tools
What We Ask
- Experience as a Data Engineer or Analytics Engineer
- Strong SQL and data modeling skills
- Experience building production data pipelines
- Understanding of cloud infrastructure and scalability
- Strong collaboration and communication skills
- Ownership mindset and attention to detail
Extra Information:
- Compensation: In consultation + equity/revenue share options
- Tools & Stack: AWS, JavaScript/TypeScript, React, Node.js, GitHub, Discord, Notion
- Work Style: Remote-first, async-friendly, outcome-driven
- Growth Path: Opportunity to become Head of Data
Future Career Path:
1. Intern / Junior Data Engineer
Foundation stage: learning data fundamentals, tools, and professional habits
Technical Skills
- SQL fundamentals
- Basic Python and scripting
- Data structures and formats (JSON, CSV, Parquet)
Data Platform Skills
- Intro to cloud data services
- Basic ETL concepts
- Data quality and documentation fundamentals
Analytics Support
- Supporting dashboards and reports
- Assisting with pipeline maintenance
Professional Habits
- Curiosity and learning mindset
- Clear documentation and communication
- Attention to data accuracy and ethics
2. Mid-Level Data Engineer / Associate Data Engineer
Ownership stage: building reliable pipelines and enabling analytics
Technical Skills
- Advanced SQL and data modeling
- Python-based data pipelines
- Version control and CI for data
Data Platform Skills
- Managing data warehouses and orchestration tools
- Monitoring, testing, and alerting
- Cost and performance optimization
Analytics & Product Collaboration
- Supporting product, growth, and business analytics
- Enabling experimentation and metrics tracking
Professional Growth
- Mentoring junior engineers
- Leading data initiatives and improvements
3. Senior Data Engineer / Data Platform Lead / Chief Data Officer (CDO)
Leadership stage: defining data strategy and organizational impact
Advanced Data Engineering
- Designing scalable data architectures
- Streaming, real-time, and event-driven systems
Platform & Governance
- Data governance, privacy, and compliance leadership
- Tooling and architecture roadmap ownership
Leadership & Mentorship
- Leading data teams and developing talent
- Influencing product and business strategy
Strategic Impact
- Making data a core competitive advantage
- Driving company-wide data literacy
- Aligning data strategy with long-term growth