We are representing our client in the global technology and engineering sector to look for an experienced Solution Architect to design and lead the implementation of data-driven solutions leveraging platforms . This role requires a strong grasp of enterprise data ecosystems, analytics enablement, and solution delivery across cloud and on-prem environments.
You will work closely with business leaders, technical teams, and external partners to architect scalable, secure, and efficient solutions that support data integration, virtualization, analytics, and multimedia processing use cases.
Requirements
- Architect end-to-end solutions that meet both business and technical requirements, focusing on data virtualization, advanced analytics, and media workflows.
- Lead solution design using tools like Denodo, Dataiku, and FFmpeg, ensuring interoperability, performance, and scalability.
- Translate business needs into technical architecture and solution blueprints across data ingestion, transformation, modeling, and visualization layers.
- Collaborate with Data Engineers, Architects, Developers, and Stakeholders to drive the successful implementation of solutions.
- Conduct solution assessments, identify risks and gaps, and propose technical alternatives where necessary.
- Support pre-sales or early engagement discussions with clients or stakeholders where solution design is needed.
- Provide governance, review, and guidance on ongoing project delivery to ensure adherence to architecture principles and standards.
- Stay updated on emerging technologies and trends in data, AI/ML, and media processing, evaluating their potential fit.
Requirements
- Minimum 6 years of experience in solution architecture, systems integration, or enterprise architecture roles.
- Proven experience in designing and implementing solutions using: Denodo or similar data virtualization platforms, Dataiku or similar analytics or data science platforms, FFmpeg or tools for multimedia data ingestion and processing
- Strong knowledge of data platforms (e.g., data warehouses, data lakes), cloud services (AWS, GCP, or Azure), and modern data stacks.
- Strong understanding of data integration patterns, API design, and performance optimization techniques.
- Ability to balance technical depth with business understanding to recommend practical solutions.
- Excellent communication and stakeholder management skills, with the ability to present to both technical and non-technical audiences.