Senior Data Engineer (Databricks)

We're not a strategy firm that ships slide decks and walks away. Not a tech consultancy that builds what won't get adopted. Not a product company chasing problems it doesn't understand. We're all three at once: strategy, deep technical and integration expertise, and product, working as one. That combination is our flywheel. Consulting keeps us close to the hardest real-world problems. Products let us solve them at scale. Every engagement sharpens our products; every deployment makes the next engagement faster, deeper, and more certain.

We're obsessed with outcomes. While 95% of enterprise AI pilots never reach production, Visium is built to be the 5% delivering productised AI that compounds in value, not point solutions that deliver marginal gains. We are AI-native, not AI-adjacent. We don't bolt AI onto broken workflows; we redesign them with AI at the core.

As a Senior Data Engineer, you will play a key role in designing, building, and scaling modern data platforms for our clients.

You will:

• Assess and understand clients’ data landscapes, including sources, architectures, and data quality
• Collaborate with business and IT stakeholders to translate requirements into robust data solutions
• Design, build, and maintain scalable data platforms (pipelines, data lakes, data warehouses) on modern cloud infrastructures
• Implement data models, schemas, and governance frameworks to support analytics and reporting needs
• Contribute to technical sales and pre-sales activities, including solution design and estimations
• Work with large-scale, distributed data systems, troubleshoot issues, and stay current with data engineering best practices

In order to apply, this should be part of your background:

• 5+ years in Data Engineering with expertise in Data Platforms, Data Modeling, and building production-grade pipelines
• Strong ability to translate business requirements to tech solutions
• Experience with either Databricks or Microsoft Fabric is required; experience with both is a strong advantage.
• Experience with integration of SAP data
• Leadership mindset and experience in managing data engineering teams
• Skilled in distributed data processing (e.g., Spark), data lakes/warehouses, ETL/ELT patterns, and Python development
• Strong problem-solving, ownership, and consulting communication skills, able to work independently in complex environments
• Fluency in English is a must, French/German is nice to have