Senior Data Warehouse Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Warehouse Engineer based in Switzerland. This role offers the opportunity to shape the data infrastructure supporting a high-growth technology platform focused on online security and fraud detection. You will design and optimize scalable data warehouses, reliable pipelines, and modern ELT processes that enable analytics and data-driven decision-making. Working closely with data scientists, analysts, and engineers, you will transform complex data into trusted and actionable insights. The position combines hands-on engineering with opportunities to improve performance, reliability, cost efficiency, and developer productivity. You will work with modern cloud technologies including ClickHouse, Redshift, AWS, Kafka, dbt, and Prefect. This is a strong opportunity for an autonomous data engineer who enjoys solving complex problems in a globally distributed, fully remote environment. Accountabilities: - Architect, build, and maintain scalable, high-performance data warehouse solutions that support analytics and operational needs. - Develop reliable, well-documented data pipelines and ELT processes while maintaining strong standards for data quality and consistency. - Optimize data warehouse performance through query optimization, partitioning, indexing, and other performance-tuning techniques. - Partner with data analysts and data scientists to transform raw data into actionable analytics and support machine learning initiatives. - Monitor, troubleshoot, and continuously improve data warehouse infrastructure while balancing performance, reliability, and cost efficiency. - Establish and promote best practices for clean, well-structured, reliable, and accessible data. - Work with modern cloud-based data warehouses such as ClickHouse and integrate data platforms with other cloud services. - Contribute to developer-facing data tools and solutions that empower engineering and other technical teams.

- Support data transformation and modeling initiatives using tools such as dbt and SQL. - Contribute to automation, testing, version control, code reviews, and other software engineering practices across data systems. - Help improve the scalability, maintainability, and operational efficiency of the overall data platform. Requirements: - Extensive professional experience designing, implementing, and optimizing data warehouses in cloud environments such as AWS or GCP. - Strong hands-on expertise with data modeling and transformation tools, particularly dbt. - Excellent SQL skills and experience with modern columnar or cloud data warehouse technologies such as ClickHouse, Databricks, BigQuery, Snowflake, or Redshift. - Experience developing and managing data pipelines using orchestration tools such as Prefect or Airflow. - Solid understanding of data engineering principles, warehouse architecture, transformation, and data quality. - Strong software engineering fundamentals, including version control, code reviews, testing, automation, and maintainable development practices. - Experience working collaboratively with data scientists, analysts, engineers, and other cross-functional stakeholders. - Strong English communication skills for effective collaboration within a globally distributed remote team. - High degree of ownership, autonomy, and accountability, with the ability to work effectively in ambiguous environments. - Strong analytical and problem-solving skills, with a practical approach to troubleshooting and performance optimization. - Familiarity with business intelligence and visualization tools such as Apache Superset, Sigma, Tableau, or Looker is a plus. - Experience with infrastructure-as-code tools such as Terraform and a DevOps-oriented mindset is desirable. - Scripting or automation experience with Bash, Python, or Go is an advantage.