We are seeking a Senior Data Engineer with strong experience in Snowflake-based data platforms to design, build, and operate scalable, cloud-native data solutions. This role requires deep hands-on expertise across data architecture, ETL/ELT pipelines, cloud infrastructure, and data modelling, with the ability to take full technical ownership of complex projects. You will work in an international environment, contributing to architecture decisions, engineering standards, and delivery excellence across multiple data initiatives.Responsibilities: Design, implement, and maintain end-to-end data platforms using Snowflake as the core analytical engine. Lead the development of scalable, fault-tolerant ETL/ELT pipelines for large-volume and high-velocity data. Build data solutions from initial design through production, with minimal supervision. Implement data transformation and modelling layers using DBT (Core / Cloud) following analytics engineering best practices. Develop distributed data processing jobs using Apache Spark (Python or Scala). Design and optimize Snowflake schemas, warehouses, and performance strategies (clustering, caching, cost control). Ensure high standards of code quality, testing, observability, and documentation. Implement and maintain CI/CD pipelines for data workflows and transformations. Collaborate closely with product, analytics, and engineering teams in an Agile environment. Contribute to technical standards, architectural guidelines, and best practices across the data platform. Troubleshoot performance, data quality, and reliability issues in production environments. Requirements4+ years of professional experience in Data Engineering or similar roles. Strong, hands-on experience with Snowflake in production environments. Solid experience with Python or Scala, particularly in data-intensive applications. Proven experience developing and operating Apache Spark pipelines. Strong experience with cloud platforms (Azure or AWS), including native data services. Hands-on experience implementing CI/CD for data pipelines. Experience with data testing strategies (unit, integration, data validation). Strong knowledge of SQL, including performance optimization and complex transformations. Experience using DBT for data transformation, modelling, and dependency management. Experience designing and maintaining large-scale data pipelines. Ability to work autonomously and take technical ownership of deliverables. Hands-on experience with Infrastructure as Code (IaC), particularly using Terraform.Proven experience designing, implementing, and maintaining CI/CD pipelines for data workflows. Knowledge of NoSQL data stores. Experience with data governance, lineage, and metadata management. Familiarity with cost optimization strategies in cloud data platforms.