Senior Data Engineer (employee or freelance)

About the role

Who we are : 
 
We’re Qover, a leading insurtech scale-up that has raised $70 million.
With an international team of 160+ colleagues based in Brussels, we help companies orchestrate digital embedded insurance experiences.
 
Since Qover was founded in 2016, our co-founders had a clear vision of the future of insurance: it must be simple, transparent and accessible across borders – a global safety net 🌍
 
We’re well on our way to building that safety net, with a platform that protects millions of users across 32 European countries. We work with top brands like Revolut, Mastercard, BMW, Canyon, Monzo and many others.
 
Visit our website for more about what we do!

🚀 About the Role & Mission
At Qover, we are building the orchestration engine for the future of embedded insurance. Our data team operates with a pure engineering mindset and a strong focus on operational excellence—ensuring our international insurance programs run seamlessly on fresh, reliable data.
We are urgently seeking a Senior Data Engineer for a high-impact project. Ywill be in the driver’s seat: owning complex data financial reporting from prototyping directly into production, maintaining best-in-class engineering standards, and keeping our data architecture lean and scalable.
🛠️ The Tech Environment
Data Warehouse: Google BigQuery
Transformation & Ingestion: dbt, Airbyte
Languages & Scripting: Python, SQL, Bash
BI & Data Visualization: Looker
DevOps & Quality: Git, Docker, CI/CD, Unit & Integration Testing
AI-First Culture: We actively encourage leveraging AI agents to accelerate coding, testing, and deployment.
 🔑 Key Responsibilities
1. Data Financial Reporting & Pipelines
Build, maintain, and optimize robust dbt data pipelines that power the day-to-day operations of our embedded insurance programs.
Architect flexible data models designed to handle the nuances of insurance operations with minimal rework as new products launch.
Streamline BigQuery data structures to eliminate redundancy and prevent data fragmentation across systems.
 2. Data Governance & Quality Assurance
Implement automated quality checks, anomaly detection, unit tests, and integration testing.
Maintain strict data security, privacy controls, clear data lineage, and precise access management for sensitive insurance and financial data.
 3. Technical Leadership & Operations
Partner with the broader data team to push our data warehouse architecture to the next level.
Champion best practices through code reviews, technical sharing sessions, and documentation.
Empower business stakeholders to become self-serve and data-savvy.
 🎯  Your Profile
Must-Haves:
5+ years of hands-on experience in SQL and complex Data Modeling.
Proven expertise in dbt and production Python.
Strong background working with modern cloud platforms and serverless data warehouses (BigQuery highly preferred).
Solid engineering practices: comfortable with Git, Bash, Docker, CI/CD pipelines, and writing unit/integration tests.
Pragmatic mindset: You comfortably balance architectural elegance with speed of execution to hit fast-paced business deadlines.
High degree of autonomy—able to thrive in dynamic environments with minimal supervision.
Excellent communication skills; fluent in English.
 Nice-to-Haves:
Master’s degree in STEM.
Professional working proficiency in Dutch.
Direct experience in FinTech, InsurTech, or financial reporting systems.