Data Engineer | Hybrid in Madrid | Professional Standard of English Required | Open to re-locators | Sponsorship available for the right candidate
Our client is a growing technology consultancy who is expanding its existing engineering team in Madrid and is looking for talented Data Engineers to join the business. You'll work across a range of large-scale digital and data transformation programmes, helping clients design, build and modernise data platforms that support advanced analytics, reporting and business decision-making.
The Role
You'll work across a variety of projects and industries, making this an adecuado role for someone who enjoys solving complex technical problems, learning new technologies and working closely with clients and stakeholders.
Responsibilities
- Design, develop and maintain scalable data pipelines and platforms
- Build robust, production-grade data applications and solutions
- Integrate data from internal and external sources
- Ensure data quality, reliability, security and accessibility
- Support analytics, reporting and data modelling initiatives




- Work closely with engineers, analysts, consultants and business stakeholders
- Identify opportunities to improve data processes and engineering practices
- Contribute to best practices across the wider engineering team

What We're Looking For
- 4+ years of professional experience in Data Engineering
- University degree in relevant subject equivalent to 3.3 GPA+ or 2:1
- Strong programming, SQL and data engineering fundamentals
- Experience building and supporting production-grade data solutions
- Understanding of modern cloud-based data architectures
- Strong communication and stakeholder management skills
- A proactive approach to problem-solving and continuous improvement
- Ability to learn quickly and adapt to new technologies and environments
- Comfortable working in a fast-paced consultancy environment
- Experience within consulting, financial services or other regulated industries would be

📌 Data Engineer (Madrid)
🏢 Develop
📍 Madrid