Senior Data Engineer

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

We are looking for an experienced Senior Data Engineer to help design, build, and optimize modern data solutions. You will work on scalable batch and streaming pipelines, ensure high standards of data governance and security, and contribute to a cloud-based data platform used for analytics and AI.

Our preferred platforms are Databricks, Fabric, Snowflake, AWS, and GCP (in that order). If you have experience in Azure data services, that knowledge is highly relevant and transferable to Fabric.

You will thrive in this role if you are:  

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing  
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus)

Role responsibilities

• Build & Optimize Pipelines: Develop reliable batch and streaming data pipelines using Spark, Delta Lake, and modern frameworks.
• Data Platform Engineering: Implement ingestion, transformation, and curation workflows across Databricks, Fabric, Snowflake, AWS, or GCP.
• Model Data: Design logical and physical models that support analytics, AI, and business processes.
• Orchestrate Workflows: Use orchestration tools like Lakeflow, Airflow, dbt, or equivalent to manage end-to-end data processes.
• Governance & Security: Apply best practices for data governance, lineage, and secure access.
• Collaborate: Partner with data scientists, analysts, and business stakeholders to deliver data solutions that meet real-world needs.
• Optimize: Monitor and tune pipelines and infrastructure for scalability, re