Role Description
We are still looking for the very Top Talent…and we would be delighted if you were to join our team
More in details, UST is a multinational company based in North America, certified as a Top Employer company with over 35.000 employees all over the world and presence in more than 35 countries. We are leaders on digital technology services, and we provide large-scale technologic solutions to big companies.
What are we looking for?
We are seeking a hands-on Data Engineer with strong expertise in Snowflake and DBT , passionate about transforming telemetry, log, and event data into trusted insights.
High english level is required.
Key Responsabilities
• Design, develop and maintain scalable data solutions using modern cloud technologies.
• Develop and optimize data pipelines and data integration processes.
• Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
• Deliver well-structured, tested and maintainable software.
• Contribute to continuous improvement initiatives and strategic development activities.
• Apply DevOps practices, automated deployments and source control processes.
What UST expects from you?
• Strong SQL database development skills.
• Experience with Azure Data Factory, DBT and Python.
• Hands-on development experience with Snowflake.
• Knowledge of DevOps practices, automated deployments and source control tools (Azure DevOps, GitHub Actions, Git).
• Expertise in performance tuning for very large datasets.
• Broad technical understanding to identify optimal solutions.
• Ability to deliver well-structured, tested software.
• Skilled in stakeholder engagement and relationship management.
• Strong problem-solving skills with logical and structured thinking.
• Ability to design solutions that can be transitioned to first-line support teams.
Nice to have
• Background in Financial Services and data-related domains.
• Development experience with .NET and Azure.
• Familiarit
📌 Data Engineer with Snowflake and DBT (Madrid)
🏢 Ust
📍 Madrid